Development and Validation of a Novel Circulating miRNA-Based Diagnostic Score for Early Detection of Hepatocellular Carcinoma

Hepatocellular Carcinoma: The Search for an Optimal Screening Test

Hepatocellular carcinoma (HCC) is the sixth most common cancer worldwide and the third leading cause of cancer-related death, with a 5-year survival rate of 10%-12%. It usually develops in the setting of chronic liver disease (CLD), with chronic viral hepatitis, alcohol, and non-alcoholic fatty liver disease (NAFLD) being the most common risk factors. Some patients are at higher risk of developing hepatocellular cancer, so it is important to screen them regularly to diagnose the disease at an early stage and improve their chances for curative treatment. Six-monthly ultrasound with or without alpha-fetoprotein (AFP) is the currently recommended surveillance method. AFP has been used as a biomarker for liver cancer; however, it has low sensitivity and specificity, which necessitates the search for other, more accurate biomarkers. Promising biomarkers include lens culinaris agglutinin-reactive AFP, des-gamma-carboxy prothrombin, methylated DNA markers, plasma microRNA expression, circulating tumor DNA, and circulating tumor cells. In addition, combinations of biomarkers, like the GALAD score and the Doylestown algorithm, may help in the early detection of HCC. In this review, we summarize the screening tests for early detection of HCC that have been studied over the last decade.

What are the changes in the hotspots and frontiers of microRNAs in hepatocellular carcinoma over the past decade?

BACKGROUND

Emerging research suggests that microRNAs (miRNAs) play an important role in the development of hepatocellular carcinoma (HCC). A comprehensive analysis of recent research concerning miRNAs in HCC development could provide researchers with a valuable reference for further studies.

AIM

To make a comprehensive analysis of recent studies concerning miRNAs in HCC.

METHODS

All relevant publications were retrieved from the Web of Science Core Collection database. Bibliometrix software, VOSviewer software and CiteSpace software were used to visually analyze the distribution by time, countries, institutions, journals, and authors, as well as the keywords, burst keywords and thematic map.

RESULTS

A total of 9426 publications on this topic were found worldwide. According to the keywords analysis, we found that the studies of miRNAs focused on their expression level, effects, and mechanisms on the biological behaviour of HCC. Keywords bursting analysis showed that in the early years (2013-2017), "microRNA expression", "gene expression", "expression profile", "functional polymorphism", "circulating microRNA", "susceptibility" and "mir 21" started to attract attention. In the latest phase (2018-2022), the hot topics turned to "sorafenib resistance", "tumor microenvironment" and so on.

CONCLUSION

This study provides a comprehensive overview of the role of miRNAs in HCC development based on bibliometric analysis. The hotspots in this field focus on miRNAs expression level, effects, and mechanisms on the biological behavior of HCC. The frontiers turned to sorafenib resistance, tumor microenvironment and so on.

Identification of a novel miRNA-based recurrence and prognosis prediction biomarker for hepatocellular carcinoma

Background

A high recurrence rate has always been a serious problem for treatment of hepatocellular carcinoma (HCC). Exploring predictors of postoperative and posttransplantation recurrence in patients with HCC can guide treatment strategies for clinicians.

Results

In this study, logistic regression and multivariate Cox regression models were constructed with microRNA expression profile data from The Cancer Genome Atlas (TCGA) and gene expression omnibus (GEO). The accuracy of predictions was assessed using receiver operating characteristic curve (ROC) and Kaplan‒Meier survival curve analyses. The results showed that the combination of 10 miRNAs (including hsa-miR-509-3p, hsa-miR-769-3p, hsa-miR-671-3p, hsa-miR-296-5p, hsa-miR-767-5p, hsa-miR-421, hsa-miR-193a-3p, hsa-miR-139-3p, hsa-miR-342-3p, and hsa-miR-193a-5p) accurately predicted postoperative and posttransplantation malignancy recurrence in HCC patients and was also valuable for prognostic evaluation of HCC patients. The 10-miRNA prediction model might assist doctors in making prognoses for HCC patients who have a high probability of relapse following surgery and in offering additional, individualized treatment to lessen that risk.

Overview of MicroRNAs as Diagnostic and Prognostic Biomarkers for High-Incidence Cancers in 2021

MicroRNAs (miRNAs) are small non-coding RNAs (ncRNAs) about 22 nucleotides in size, which play an important role in gene regulation and are involved in almost all major cellular physiological processes. In recent years, the abnormal expression of miRNAs has been shown to be associated with human diseases including cancer. In the past ten years, the link between miRNAs and various cancers has been extensively studied, and the abnormal expression of miRNAs has been reported in various malignant tumors, such as lung cancer, gastric cancer, colorectal cancer, liver cancer, breast cancer, and prostate cancer. Due to the high malignancy grade of these cancers, it is more necessary to develop the related diagnostic and prognostic methods. According to the study of miRNAs, many potential cancer biomarkers have been proposed for the diagnosis and prognosis of diseases, especially cancer, thus providing a new theoretical basis and perspective for cancer screening. The use of miRNAs as biomarkers for diagnosis or prognosis of cancer has the advantages of being less invasive to patients, with better accuracy and lower price. In view of the important clinical significance of miRNAs in human cancer research, this article reviewed the research status of miRNAs in the above-mentioned cancers in 2021, especially in terms of diagnosis and prognosis, and provided some new perspectives and theoretical basis for the diagnosis and treatment of cancers.

Identification and Validation of a Novel Immune Infiltration-Based Diagnostic Score for Early Detection of Hepatocellular Carcinoma by Machine-Learning Strategies

Objective

To investigate the diagnostic gene biomarkers for hepatocellular carcinoma (HCC) and identify the immune cell infiltration characteristics in this pathology.

Methods

Five gene expression datasets were obtained through Gene Expression Omnibus (GEO) portal. After batch effect removal, differentially expressed genes (DEGs) were conducted between 209 HCC and 146 control tissues and functional correlation analyses were performed. Two machine learning algorithms were used to develop diagnostic signatures. The discriminatory ability of the gene signature was measured by AUC. The expression levels and diagnostic value of the identified biomarkers in HCC were further validated in three independent external cohorts. CIBERSORT algorithm was adopted to explore the immune infiltration of HCC. A correlation analysis was carried out between these diagnostic signatures and immune cells.

Results

A total of 375 DEGs were identified. GPC3, ACSM3, SPINK1, COL15A1, TP53I3, RRAGD, and CLDN10 were identified as the early diagnostic signatures of HCC and were all validated in external cohorts. The corresponding results of AUC presented excellent discriminatory ability of these feature genes. The immune cell infiltration analysis showed that multiple immune cells associated with these biomarkers may be involved in the development of HCC.

Conclusion

This study indicates that GPC3, ACSM3, SPINK1, COL15A1, TP53I3, RRAGD, and CLDN10 are potential biomarkers associated with immune infiltration in HCC. Combining these genes can be used for early detection of HCC and evaluating immune cell infiltration. Further studies are needed to explore their roles underlying the occurrence of HCC.

The Potential Role of miRNAs in Cognitive Frailty

Frailty is an aging related condition, which has been defined as a state of enhanced vulnerability to stressors, leading to a limited capacity to meet homeostatic demands. Cognitive impairment is also frequent in older people, often accompanying frailty. Age is the main independent risk factor for both frailty and cognitive impairment, and compelling evidence suggests that similar age-associated mechanisms could underlie both clinical conditions. Accordingly, it has been suggested that frailty and cognitive impairment share common pathways, and some authors proposed "cognitive frailty" as a single complex phenotype. Nevertheless, so far, no clear common underlying pathways have been discovered for both conditions. microRNAs (miRNAs) have emerged as key fine-tuning regulators in most physiological processes, as well as pathological conditions. Importantly, miRNAs have been proposed as both peripheral biomarkers and potential molecular factors involved in physiological and pathological aging. In this review, we discuss the evidence linking changes of selected miRNAs expression with frailty and cognitive impairment. Overall, miR-92a-5p and miR-532-5p, as well as other miRNAs implicated in pathological aging, should be investigated as potential biomarkers (and putative molecular effectors) of cognitive frailty.