Identification of potential biomarkers for hepatocellular carcinoma based on machine learning and bioinformatics analysis.

Metastasis is the major cause of hepatocellular carcinoma (HCC) mortality. But the effective biomarkers for HCC metastasis remain underexplored. Here we integrated GEO (Gene Expression Omnibus) and TCGA (The Cancer Genome Atlas) datasets to screen candidate genes for hepatocellular carcinoma metastasis, a consensus metastasis-derived prognostic signature (MDPS) was constructed by machine learning.

Degradation of PARP1 by MARCHF3 in tumor cells triggers cCAS-STING activation in dendritic cells to regulate antitumor immunity in hepatocellular carcinoma.

Background: Resistance to immune checkpoint inhibitors (ICIs) significantly limits the efficacy of immunotherapy in patients with hepatocellular carcinoma (HCC). However, the mechanisms underlying immunotherapy resistance remain poorly understood. Our aim was to clarify the role of membrane-associated ring-CH-type finger 3 (MARCHF3) in HCC within the framework of anti-programmed cell death protein-1 (PD-1) therapy.

Identifying epithelial-mesenchymal transition-related genes as prognostic biomarkers and therapeutic targets of hepatocellular carcinoma by integrated analysis of single-cell and bulk-RNA sequencing data.

Background: Hepatocellular carcinoma (HCC) remains one of the most lethal cancers globally. Patients with advanced HCC tend to have poor prognoses and shortened survival. Recently, data from bulk RNA sequencing have been employed to discover prognostic markers for various cancers.

Establishment of a circRNA-regulated E3 ubiquitin ligase signature and nomogram to predict immunotherapeutic efficacy and prognosis in hepatocellular carcinoma.

Background: Hepatocellular carcinoma (HCC) is a common type of malignant tumor where the prognosis is dismal. Circular RNA (CircRNA) is a novel RNA that regulates downstream gene transcription and translation to influence the progression of HCC. However, the regulatory relationship that exists between E3 ligases, which is a class of post-translational modifying proteins, and circRNA remains unclear.

Effects of Indocyanine Green (ICG) Imaging-Assisted Cholecystectomy on Intraoperative and Postoperative Complications: A meta-Analysis.

Background: Accurate recognition of Calot's triangle during cholecystectomy is important in preventing intraoperative and postoperative complications. The use of indocyanine green (ICG) fluorescence imaging has become increasingly prevalent in cholecystectomy procedures. Our study aimed to evaluate the specific effects of ICG-assisted imaging in reducing complications.

TRIM5 as a promising diagnostic biomarker of hepatocellular carcinoma: integrated analysis and experimental validation.

The TRIM family is associated with the membrane, and its involvement in the progression, growth, and development of various cancer types has been researched extensively. However, the role played by the TRIM5 gene within this family has yet to be explored to a great extent in terms of hepatocellular carcinoma (HCC). The data of patients relating to mRNA expression and the survival rate of individuals diagnosed with HCC were extracted from The Cancer Genome Atlas (TCGA) database.

Causal associations between gut microbiota and primary biliary cholangitis: a bidirectional two-sample Mendelian randomization study.

Background: Previous studies have suggested an association between gut microbiota and primary biliary cholangitis (PBC). Nonetheless, the causal relationship between gut microbiota and PBC risk remains unclear.

Methods: A bidirectional two-sample Mendelian Randomization (MR) study was employed using summary statistical data for gut microbiota and PBC from the MiBioGen consortium and Genome-Wide Association Studies (GWAS) database to investigate causal relationships between 211 gut microbiota and PBC risk.

A Novel Scoring Model of Deubiquitination Patterns Predicts Prognosis and Immunotherapeutic Response in Hepatocellular Carcinoma.

Aberrant expression of deubiquitinases (DUBs) is significantly associated with tumorigenesis. However, the precise impact of deubiquitination on the tumour microenvironment (TME) and immunotherapy in hepatocellular carcinoma (HCC) remains unclear. In this study, we comprehensively characterized the transcriptional and genetic alterations of 26 overall survival (OS)-related DUBs in HCC.

In vivo CRISPR screen identifies LTN1 as a novel tumor suppressor ubiquitinating insulin-like growth factor 2 mRNA-binding protein 1 in hepatocellular carcinoma.

Background And Aims: Hepatocellular carcinoma (HCC) is a frequent and aggressive kind of cancer. Although E3 ligases play important roles in HCC development, several E3 ligases remain unknown.

Approach And Results: Through in vivo CRISPR knockout (KO) screens targeting related E3 ligase genes in HCC nude mice models, we discovered LTN1 as a novel tumor suppressor in HCC.

RNF173 suppresses RAF/MEK/ERK signaling to regulate invasion and metastasis via GRB2 ubiquitination in Hepatocellular Carcinoma.

Background: The role of the membrane-associated RING-CH (MARCH) family in carcinogenesis has been widely studied, but the member of this family, RNF173, has not yet been thoroughly explored in the context of hepatocellular carcinoma (HCC).

Methods: With the use of an HCC tissue microarray and IHC staining, we aim to determine the differential expression of RNF173 in HCC patients and its clinical significance. The biological role of RNF173 is investigated through in vitro and in vivo experiments.

Screening and Verification of Key Ubiquitination Genes Related to Immune Infiltration in Stage III/IV Hepatocellular Carcinoma.

Introduction: Immune checkpoint therapy (ICIs) effectively improves the prognosis of advanced (stage III/IV) hepatocellular carcinoma (HCC) patients. However, its objective response rate (ORR) is below 20%, significantly limiting ICI use in advanced HCC patients. The level of tumour immune infiltration influences ICI response rate.

Identification of the mitophagy-related diagnostic biomarkers in hepatocellular carcinoma based on machine learning algorithm and construction of prognostic model.

Background And Aims: As a result of increasing numbers of studies most recently, mitophagy plays a vital function in the genesis of cancer. However, research on the predictive potential and clinical importance of mitophagy-related genes (MRGs) in hepatocellular carcinoma (HCC) is currently lacking. This study aimed to uncover and analyze the mitophagy-related diagnostic biomarkers in HCC using machine learning (ML), as well as to investigate its biological role, immune infiltration, and clinical significance.

Comprehensive analysis of the clinical significance, immune infiltration, and biological role of MARCH ligases in HCC.

The membrane-associated RING-CH (MARCH) family, a member of the E3 ubiquitin ligases, has been confirmed by a growing number of studies to be associated with immune function and has been highlighted as a potential immunotherapy target. In our research, hepatocellular carcinoma (HCC) patients were divided into C1 and C2 MARCH ligase-related patterns by the non-negative matrix factorization (NMF) algorithm. Multiple analyses revealed that the MARCH ligase-related cluster was related to prognosis, clinicopathological characteristics, and the tumor immune microenvironment (TIME).

Bioinformatics analysis of immune infiltrates and tripartite motif () family genes in hepatocellular carcinoma.

Background: The tripartite motif () family are important members of the Gene-finger-containing E3 ubiquitin-conjugating enzyme and are involved in the progression of hepatocellular carcinoma (HCC). Previous studies have largely focused on gene expression and molecular pathways, while the underlying role of the family in the tumor immune microenvironment (TIME) remains poorly understood.

Methods: We systematically explored the correlations of prominent genes with immune checkpoints and immune infiltrates in 231 HCC samples [International Cancer Genome Consortium (ICGC) cohort (n=231); The Cancer Genome Atlas (TCGA) cohort (n=370)].

Down-regulation of circPTTG1IP induces hepatocellular carcinoma development via miR-16-5p/RNF125/JAK1 axis.

Circular RNAs are known to regulate the biological processes of hepatocellular carcinoma (HCC), and humans with Down syndrome are at low risk of developing solid tumors due to the amplification of several tumor suppressor genes on human chromosome 21 (HSA21). Here, we aimed to investigate the potential role of circRNAs originating from HSA21 in the progression of HCC. CircRNA-sequencing was performed to analyze differentially expressed circRNAs in 4 HCC and peritumor tissues, and circRNAs originating from HSA21 were further analyzed.

Impact of Socioeconomic Factors on Prognosis and Clinical Management in Patients with Hepatocellular Carcinoma.

Background: The prognosis for patient survival using the tumor-node-metastasis (TNM) staging system may be imperfect, as it based only on biological factors and does not include the socioeconomic factors (SEFs). We integrated the SEFs into the TNM system (TNMSEF), and evaluated whether the novel TNM-SEF staging system showed better prediction capacity and improved clinical guidance in hepatocellular carcinoma (HCC).

Methods: We selected data of 12 514 cases with HCC between 2010 and 2015 from the SEER database.

Can Patients with Pancreatic Cancer and Liver Metastases Obtain Survival Benefit from Surgery? A Population-Based Study.

Surgery for pancreatic cancer with liver metastases (PCL) is not recommended in the international guidelines, and investigation of its clinical significance in patients with PCL is very limited. This study explored whether surgery, especially synchronous resection of the primary tumor and liver metastases (SPL), could improve survival in PCL. Data of 14,248 patients with PCL from Surveillance, Epidemiology, and End Results database was analyzed.

A practical nomogram and risk stratification system predicting the cancer-specific survival for patients with early hepatocellular carcinoma.

Background: Our purpose was to establish and validate a nomogram model in early hepatocellular carcinoma (HCC) patients for predicting the cancer-specific survival (CSS).

Methods: We extracted eligible data of relevant patients between 2010 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. Further, we divided all patients into two groups (training and validation cohorts) at random (7:3).