Extracellular vesicles in hepatocellular carcinoma: unraveling immunological mechanisms for enhanced diagnosis and overcoming drug resistance

Current research is focused on utilizing EVs as a biopsy tool to improve the diagnostic accuracy of HCC, reduce surgical risk, and explore their potential in modulating drug resistance and advancing immunotherapeutic strategies. Extracellular vesicles (EVs) have been increasingly recognized as important non-invasive biomarkers in hepatocellular carcinoma (HCC) due to the presence of a variety of biomolecules within them, such as proteins and RNAs, etc. EVs play a key role in the early detection, diagnosis, treatment, and prognostic monitoring of HCC. These vesicles influence the development of HCC and therapeutic response in a variety of ways, including influencing the tumor microenvironment, modulating drug resistance, and participating in immune regulatory mechanisms. In addition, specific molecules such as miRNAs and specific proteins in EVs are regarded as potential markers for monitoring treatment response and recurrence of HCC, which have certain research space and development prospects. In this paper, we summarize the aspects of EVs as HCC diagnostic and drug resistance markers, and also discuss the questions that may be faced in the development of EVs as markers.

Safety assessment of esomeprazole: real-world adverse event signal mining and analysis based on FAERS database

BACKGROUND

Esomeprazole holds a significant position in the treatment of acid-related diseases. However, as with all drugs, it may also carry some potential risk of adverse effects. This study aims to further evaluate the safety of esomeprazole for clinical use.

RESEARCH DESIGN AND METHODS

The data of esomeprazole-related adverse events was extracted from the FAERS database from the first quarter of 2004 to the first quarter of 2024 and used Reporting Odds Ratios (ROR), Proportional Reporting Ratios (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Empirical Bayes Geometric Mean(EBGM) for data mining.

RESULTS

A total of 67,712 esomeprazole-related adverse events were extracted from the FAERS database, involving 27 system organ class. The frequency of renal and urinary occurrence was the highest, and the signal was the strongest. Additionally, we detected 324 preferred terms: rebound acid hypersecretion, nephrogenic anemia, and hyperparathyroidism secondary showed significant high signal strength. In the elderly, adverse events were concentrated in the gastrointestinal disorders system, and the most common adverse events were dyspepsia and hyponatremia. Unexpected adverse events, such as vomiting, acute kidney injury, and anaphylactic reaction occurred in children.

CONCLUSIONS

We discovered some new and special esomeprazole-related adverse events, raising awareness of the safety of esomeprazole and further helping to mitigate associated risks.

Copper metabolism-related lncRNAs predict prognosis and immune landscape in liver cancer patients

BACKGROUND

Characterized by its high mortality and easy recurrence, hepatocellular carcinoma (HCC) poses significant clinical challenges. The association between copper metabolism and development of cancer has been identified. However, the underlying mechanisms of copper metabolism-related long non-coding RNAs (CMRLs) in HCC remain elusive. To address the gap, our study analyzed the prognostic and immuno-therapeutic value of CMRLs in HCC.

METHODS

This research utilized The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) data (n=424) for analysis, applying the "limma" package in R software for differential gene analysis and construction of a prognostic signature. We validated the signature using training and validation groups stochastically divided at a ratio of 1:1 and assessed prognostic value via Kaplan-Meier, C-index, and receiver operating characteristic (ROC) curves. By multivariate Cox regression, independent prognostic indicators were identified, and a nomogram was formulated for survival forecasting. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses elucidated biological pathways, and the immune landscape was examined through multiple algorithms. Finally, drug sensitivity was determined from Genomics of Drug Sensitivity in Cancer (GDSC), with mutation analysis conducted via maftools.

RESULTS

In this study, a predictive model based on four pivotal CMRLs (PRRT3-AS1, AC108752.1, AC092115.3, AL031985.3) significantly associated with HCC progression and prognosis was constructed and validated with the overall survival (OS) prediction area under the curve (AUC) values for 1, 3, and 5 years of 0.718, 0.688, and 0.669, respectively. The calibration curves and C-index values showed a solid prognostic ability of the nomogram. The high-risk group was notably higher than the low-risk group both in OS and tumor mutational burdens (TMBs). Moreover, functional annotation enrichment analysis of CMRLs revealed that the signature was mainly associated with mitotic function, chromosome, kinetochore, cell cycle, and oocyte meiosis. Furthermore, therapeutic drugs, including fluorouracil, afatinib, alpelisib, cedranib, crizotinib, erlotinib, gefitinib, and ipatasertib, were found to induce higher sensitivity in high-risk group.

CONCLUSIONS

The prognostic signature consisting of four CMRLs displays an outstanding predictive performance and improves the precision of immuno-oncology.

Development and validation of a nomogram model for predicting the risk of MAFLD in the young population

This study aimed to develop and validate a nomogram model that includes clinical and laboratory indicators to predict the risk of metabolic-associated fatty liver disease (MAFLD) in young Chinese individuals. This study retrospectively analyzed a cohort of young population who underwent health examination from November 2018 to December 2021 at The Affiliated Hospital of Southwest Medical University in Luzhou City, Sichuan Province, China. We extracted the clinical and laboratory data of 43,040 subjects and randomized participants into the training and validation groups (7:3). Univariate logistic regression analysis, the least absolute shrinkage and selection operator regression, and multivariate logistic regression models identified significant variables independently associated with MAFLD. The predictive accuracy of the model was analyzed in the training and validation sets using area under the receiver operating characteristic (AUROC), calibration curves, and decision curve analysis. In this study, we identified nine predictors from 31 variables, including age, gender, body mass index, waist-to-hip ratio, alanine aminotransferase, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, uric acid, and smoking. The AUROC for the subjects in the training and validation groups was 0.874 and 0.875, respectively. The calibration curves show excellent accuracy of the nomogram. This nomogram which was based on demographic characteristics, lifestyle habits, anthropometrics, and laboratory data can visually and individually predict the risk of developing MAFLD. This nomogram is a quick and effective screening tool for assessing the risk of MAFLD in younger populations and identifying individuals at high risk of MAFLD, thereby contributing to the improvement of MAFLD management.

The Landscape of Acute Pancreatitis Trials Registered in ClinicalTrials.gov: A Cross-sectional Study

OBJECTIVES

Clinical studies are important in informing evidence-based practice for patients with acute pancreatitis (AP). To determine whether registered studies adequately meet this need, we leveraged the ClinicalTrials.gov database to provide an overview of studies pertaining to AP.

METHODS

ClinicalTrials.gov was searched and the search term used was AP. Analysis was restricted to studies registered before January 12, 2021.

RESULTS

Of 363,632 trials overall, 234 (0.06%) were eventually included for analysis. Interventional studies and observational studies comprised 67.5% and 32.5% of these studies respectively. Most studies were initiated 2007 or later. Endoscopic retrograde cholangiopancreatography was the single most frequent cause of AP specified in these studies (16.7%). Nearly 72% of these studies had a sample size greater than 50. With respect to study design, 87.3% of interventional studies were randomized, 53.5% were blinded. The top 3 countries with the largest number of registered studies were China (n = 59), followed by the United States (n = 53) and India (n = 12).

CONCLUSIONS

Our results indicate that the research activity falls short of what is needed in terms of the burden of AP. The distribution of these AP-related studies by global regions indicates that there exists regional disparities.

Trend of gastrointestinal and liver diseases in China: Results of the Global Burden of Disease Study, 2019

BACKGROUND

China is one of the countries with the largest burden of gastrointestinal and liver diseases (GILD) in the world. The GILD constitutes various causes of mortality and disability. The study aimed to investigate the trend of GILD in China using the Global Burden of Diseases Study 2019 (GBD 2019) data resources from 1990 to 2019.

METHODS

The data on the age-standardized mortality rates (ASMR) and disability-adjusted life years (DALYs) for GILD in China from 1990 to 2019 were collected from the GBD 2019 data resources. Furthermore, the ranking of the main causes of deaths and DALYs, as well as the trends of ASMR, DALYs, years of life lost (YLLs), and years of life lost due to disability (YLDs) per 1,000,000 in GILD were reported.

RESULTS

The ASMR and DALYs for stomach cancer, liver cancer, and esophageal cancer, which ranked top three among the GILDs from 1990 to 2019, were gradually decreasing. Significant decreases in the ASMR and DALYs were found in diarrheal diseases and acute hepatitis (A, E, and C). However, noteworthy increases were found in those of colon and rectum cancer (CRC) and pancreatic cancer. Trend of DALYs, mortality, and YLLs rates for most of GILD were decreasing from 1990 to 2019, except the burden of CRC and pancreatic cancer with an increasing trend. The DALYs, mortality and YLLs of most GILD diseases showed decreasing trends from 1990 to 2019, except the burden of CRC and pancreatic cancer with an increasing trends.

CONCLUSIONS

The result of the GBD 2019 showed that the rates of most GILDs decreased in China; however, gastrointestinal and liver cancer, such as stomach cancer still held the top ranking. Furthermore, the shift from infectious diseases to non-communicable causes among GILD burden is occurring.

Global burden of early-onset colorectal cancer among people aged 40-49 years from 1990 to 2019 and predictions to 2030

PURPOSE

To explore the disease burden of early-onset colorectal cancer (EO-CRC) in individuals aged 40-49 years and provide baseline evidence for routine recommended age adjustment for CRC screening and other clinical decision-making.

METHODS

We collected data stratified by sex, risk factors, and socio-demographic index (SDI) from the Global Burden of Disease Study 2019 Data Resources. Trends in disease burden were analyzed by estimated annual percentage change. The Bayesian age-period-cohort model predicted the burden over the following 10 years.

RESULTS

In 2019, the global rates of incidence, mortality, prevalence, and disability-adjusted life year (DALY) of EO-CRC in people aged 40-44 years were 11.48 (95% uncertainty interval: 10.50-12.59), 4.35 (4.01-4.70), 72.63 (66.48-79.52), 209.82 (193.55-226.59) per 100,000 population. For people aged 45-49 years, the rates of these four estimates were 19.63 (17.97-21.54), 7.76 (7.16-8.41), 121.73 (110.99-133.84), and 335.83 (310.14-362.91), respectively. The incidence and prevalence rates for both age groups increased while the mortality and DALY rates remained stable from 1990 to 2019. In 2019, high-income North America had the highest incidence and prevalence rates. A low milk diet accounted for the largest proportion of global DALYs in EO-CRC, and there was a tendency for the DALY rate first to increase and then decrease with increasing SDI. The incidence and mortality rates were predicted to increase in the next 10 years.

CONCLUSION

The current and future burden of EO-CRC among people aged 40-49 years is heavy. Substantial variation exists in disease burden across regions and countries. Urgent screening actions and policies are needed.

Global trends and hotspots in the field of mitochondrial dynamics and hepatocellular carcinoma: A bibliometric analysis from 2007 to 2023

BACKGROUND

Mitochondria are dynamic organelles, and mitochondrial dynamics are important for the maintenance of mitochondrial inheritance and function. Recently, an increasing number of studies have shown that mitochondrial dynamics play an important role in the occurrence and development of hepatocellular carcinoma (HCC). However, bibliometric analyses of mitochondrial dynamics in HCC are scarce. Therefore, we conducted a bibliometric analysis to explore the current global research status and trends in mitochondrial dynamics and HCC.

METHODS

Global publications on mitochondrial dynamics and HCC published between 2007 and May 2023 were retrieved from the Web of Science Core Collection (WoSCC) database. Bibliometric analysis was performed using Bibliometrix, VOSviewer, and CiteSpace to analyze the numbers, citations, countries, institutions, authors, journals, references, and keywords.

RESULTS

A total of 518 publications were retrieved fromthe WoSCC database. China and The Fourth Military Medical University were the most productive countries and institutions. Zorzano, A published the most literature whereas Chen, HC was the author with the highest number of co-citations. Plos One was the most popular journal, whereas the Journal of Biological Chemistry had the highest number of co-citations. The most frequently used keyword was "mitochondria". Further analysis of the references and keywords showed that the molecular mechanisms linking them to drug therapy targets should be the focus of future studies.

CONCLUSIONS

Research on mitochondrial dynamics in HCC has received much attention, and many studies have been published. However, research on mitochondrial dynamics and HCC has been limited by insufficient regional development imbalances and global cooperation. Nevertheless, future research on mitochondrial dynamics and HCC is promising, especially regarding the molecular mechanisms of mitochondrial fission and fusion and how to link the currently known molecular mechanisms with drug therapy targets for HCC.

Development and validation of a nomogram for predicting in-hospital mortality of intensive care unit patients with liver cirrhosis

BACKGROUND

Liver cirrhosis patients admitted to intensive care unit (ICU) have a high mortality rate.

AIM

To establish and validate a nomogram for predicting in-hospital mortality of ICU patients with liver cirrhosis.

METHODS

We extracted demographic, etiological, vital sign, laboratory test, comorbidity, complication, treatment, and severity score data of liver cirrhosis patients from the Medical Information Mart for Intensive Care IV (MIMIC-IV) and electronic ICU (eICU) collaborative research database (eICU-CRD). Predictor selection and model building were based on the MIMIC-IV dataset. The variables selected through least absolute shrinkage and selection operator analysis were further screened through multivariate regression analysis to obtain final predictors. The final predictors were included in the multivariate logistic regression model, which was used to construct a nomogram. Finally, we conducted external validation using the eICU-CRD. The area under the receiver operating characteristic curve (AUC), decision curve, and calibration curve were used to assess the efficacy of the models.

RESULTS

Risk factors, including the mean respiratory rate, mean systolic blood pressure, mean heart rate, white blood cells, international normalized ratio, total bilirubin, age, invasive ventilation, vasopressor use, maximum stage of acute kidney injury, and sequential organ failure assessment score, were included in the multivariate logistic regression. The model achieved AUCs of 0.864 and 0.808 in the MIMIC-IV and eICU-CRD databases, respectively. The calibration curve also confirmed the predictive ability of the model, while the decision curve confirmed its clinical value.

CONCLUSION

The nomogram has high accuracy in predicting in-hospital mortality. Improving the included predictors may help improve the prognosis of patients.

Development and Validation of a Dynamic Nomogram for Predicting in-Hospital Mortality in Patients with Acute Pancreatitis: A Retrospective Cohort Study in the Intensive Care Unit

PURPOSE

The aim of this study is to develop and validate a predictive model for the prediction of in-hospital mortality in patients with acute pancreatitis (AP) based on the intensive care database.

PATIENTS AND METHODS

We analyzed the data of patients with AP in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database and Electronic Intensive Care Unit Collaborative Research Database (eICU-CRD). Then, patients from MIMIC-IV were divided into a development group and a validation group according to the ratio of 8:2, and eICU-CRD was assigned as an external validation group. Univariate logistic regression and least absolute shrinkage and selection operator regression were used for screening the best predictors, and multivariate logistic regression was used to establish a dynamic nomogram. We evaluated the discrimination, calibration, and clinical efficacy of the nomogram, and compared the performance of the nomogram with Acute Physiology and Chronic Health Evaluation II (APACHE-II) score and Bedside Index of Severity in AP (BISAP) score.

RESULTS

A total of 1030 and 514 patients with AP in MIMIC-IV database and eICU-CRD were included in the study. After stepwise analysis, 8 out of a total of 37 variables were selected to construct the nomogram. The dynamic nomogram can be obtained by visiting https://model.sci-inn.com/KangZou/. The area under receiver operating characteristic curve (AUC) of the nomogram was 0.859, 0.871, and 0.847 in the development, internal, and external validation set respectively. The nomogram had a similar performance with APACHE-II (AUC = 0.841, p = 0.537) but performed better than BISAP (AUC = 0.690, p = 0.001) score in the validation group. Moreover, the calibration curve presented a satisfactory predictive accuracy, and the decision curve analysis suggested great clinical application value of the nomogram.

CONCLUSION

Based on the results of internal and external validation, the nomogram showed favorable discrimination, calibration, and clinical practicability in predicting the in-hospital mortality of patients with AP.