The clinical significance of lipopolysaccharide binding protein in hepatocellular carcinoma

A deep learning-based framework for predicting survival-associated groups in colon cancer by integrating multi-omics and clinical data

Precise prognostic classification of patients and identifying survival subgroups and their associated genes can be important clinical references when designing treatment strategies for cancer patients. Multi-omics and data integration techniques are powerful tools to achieve this goal. This study aimed to introduce a machine learning method to integrate three types of biological data, and investigate the performance of two other methods, in identifying the survival dependency of patients. The data included TCGA RNA-seq gene expression, DNA methylation, and clinical data from 368 patients with colon cancer also we use an independent external validation data set, containing 232 samples. Three methods including, hyper-parameter optimized autoencoders (HPOAE), normal autoencoder, and penalized principal component analysis (PPCA) were used for simultaneous data integration and estimation under a COX hazards model. The HPOAE was thought to outperform other methods. The HPOAE had the Log Rank Mantel-Cox value of 14.27 ± 2, and a Breslow-Generalized Wilcoxon value of 13.13 ± 1. Ten miRNA, 11 methylated genes, and 28 mRNA all by (importance of marginal cutoff > 0.95) were identified. The study demonstrated that hsa-miR-485-5p targets both ZMYM1 and tp53, the latter of which has been previously associated with cancer in numerous studies. Furthermore, compared to other methods, the HPOAE exhibited a greater capacity for identifying survival subgroups and the genes associated with them in patients with colon cancer. However, all of the results were obtained by computational methods, and clinical and experimental studies are needed to validate these results.

Intestinal Injury in Ugandan Children Hospitalized With Malaria

BACKGROUND

Severe malaria is associated with multiple organ dysfunction syndrome (MODS), which may involve the gastrointestinal tract.

METHODS

In a prospective cohort study in Uganda, we measured markers of intestinal injury (intestinal fatty-acid binding protein [I-FABP] and zonula occludens-1 [ZO-1]) and microbial translocation (lipopolysaccharide binding protein [LBP] and soluble complement of differentiation 14 [sCD14]) among children admitted with malaria. We examined their association with biomarkers of inflammation, endothelial activation, clinical signs of hypoperfusion, organ injury, and mortality.

RESULTS

We enrolled 523 children (median age 1.5 years, 46% female, 7.5% mortality). Intestinal FABP was above the normal range (≥400 pg/mL) in 415 of 523 patients (79%). Intestinal FABP correlated with ZO-1 (ρ = 0.11, P = .014), sCD14 (ρ = 0.12, P = .0046) as well as markers of inflammation and endothelial activation. Higher I-FABP levels were associated with lower systolic blood pressure (ρ = -0.14, P = .0015), delayed capillary refill time (ρ = 0.17, P = .00011), higher lactate level (ρ = 0.40, P < .0001), increasing stage of acute kidney injury (ρ = 0.20, P = .0034), and coma (P < .0001). Admission I-FABP levels ≥5.6 ng/mL were associated with a 7.4-fold higher relative risk of in-hospital death (95% confidence interval, 1.4-11, P = .0016).

CONCLUSIONS

Intestinal injury occurs commonly in children hospitalized with malaria and is associated with microbial translocation, systemic inflammation, tissue hypoperfusion, MODS, and fatal outcome.

Differential proteomic analysis of plasma-derived exosomes as diagnostic biomarkers for chronic HBV-related liver disease

Hepatitis B virus (HBV) infection is still a major public health problem worldwide. We aimed to identify new, non-invasive biomarkers for the early diagnosis of chronic HBV-related diseases, reveal alterations in the progression of chronic hepatitis B (CHB), liver cirrhosis (LC), and hepatocellular carcinoma (HCC). Here, exosomes were isolated and characterized through size exclusion chromatography and nanoparticle tracking analysis. Profiles of differentially expressed proteins (DEPs) were analyzed through liquid chromatography-tandem mass spectrometry (LC–MS/MS), Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes analyses. Results showed that the DEPs, including CO9, LBP, SVEP1, and VWF levels in extracellular vesicles (EVs) were significantly higher in CHB than in healthy controls (HCs). VWF expression levels in EVs were significantly lower in CHB than in those with LC. KV311 expression levels in EVs were significantly higher, whereas LBP levels were significantly lower in patients with CHB than in those with HCC. All biomarkers seemed to exhibit a high diagnostic capacity for HBV-related liver disease. Patients with HBV-induced chronic liver disease exhibit characteristic protein profiles in their EVs. Thus, serum exosomes may be used as novel, liquid biopsy biomarkers to provide useful clinical information for the diagnosis of HBV-related liver diseases at different stages.

Nimbolide attenuates gut dysbiosis and prevents bacterial translocation by improving intestinal barrier integrity and ameliorating inflammation in hepatocellular carcinoma

Gut microbiota imbalance plays a key pathological role in hepatocellular carcinoma (HCC) progression; however, the mechanism is poorly understood. We previously showed nimbolide impede tumor development by improving hepatic tight junction (TJ) proteins expression and attenuating inflammation in HCC mice. Here, we aimed to study the role of nimbolide in regulating gut microbiota imbalance and bacterial translocation (BT) through modulating intestinal TJ proteins in an experimental hepatocarcinogenesis. Nimbolide (6 mg/kg) was administered orally for 4 weeks following induction of HCC in mice at the 28th week. Nimbolide treatment attenuated the gut microbiota imbalance by decreasing 16 s rRNA levels of Escherichia coli, Enterococcus, Bacteroides and increasing Bifidobacterium, and Lactobacillus in the intestinal tissue, which was otherwise altered in HCC mice. Furthermore, nimbolide improved intestinal barrier integrity in HCC mice by upregulating TJ proteins such as occludin and ZO-1 expression and subsequently prevented hepatic BT and decreased BT markers such as LBP, sCD14, and procalcitonin in the plasma of HCC mice. Moreover, nimbolide ameliorated intestinal and hepatic inflammation by downregulating TLR4, MyD88, and NF-κB protein expression in HCC mice. Thus, nimbolide represents a novel therapeutic drug for HCC treatment by targeting the gut-liver axis, which plays an imperative role in HCC pathogenesis.

The Emerging Influences of Alpha-Fetoprotein in the Tumorigenesis and Progression of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the sixth most common cancer worldwide, and its mortality rate is the third-highest, after lung cancer and colorectal cancer. Currently, systematic targeted therapies for HCC mainly include multiple kinase inhibitors and immunotherapy. However, these drugs carry a black-box warning about the potential for inducing severe toxicity, and they do not significantly prolong the survival period of patients due to the highly heterogeneous characteristics of HCC etiology. In order to improve the prediction, effective treatment and prognosis of HCC, the tools and different biomarkers in clinical practices are recommended. Alpha-fetoprotein (AFP) is the earliest and the most widely used serum marker in the detection of HCC. Interestingly, serum AFP and cytoplasmic AFP show different, even opposite, roles in the cancer progression of HCC. This review focuses on biological characteristics, regulatory mechanisms for gene expression, emerging influences of AFP in HCC and its possible implications in HCC-targeted therapy.