A microRNA expression profile for vascular invasion can predict overall survival in hepatocellular carcinoma

Construction of a ceRNA network to reveal a vascular invasion associated prognostic model in hepatocellular carcinoma

The aim of this study is to explore the prognostic value of vascular invasion (VI) in hepatocellular carcinoma (HCC) by searching for competing endogenous RNAs (ceRNA) network and constructing a new prognostic model for HCC. The differentially expressed genes (DEGs) between HCC and normal tissues were identified from GEO and TCGA. StarBase and miRanda prediction tools were applied to construct a circRNA-miRNA-mRNA network. The DEGs between HCC with and without VI were also identified. Then, the hub genes were screened to build a prognostic risk score model through the method of least absolute shrinkage and selection operator. The prognostic ability of the model was assessed using the Kaplan-Meier method and Cox regression analysis. In result, there were 221 up-regulated and 47 down-regulated differentially expressed circRNAs (DEcircRNAs) in HCC compared with normal tissue. A circRNA-related ceRNA network was established, containing 11 DEcircRNAs, 12 DEmiRNAs, and 161 DEmRNAs. Meanwhile, another DEG analysis revealed 625 up-regulated and 123 down-regulated DEGs between HCC with and without VI, and then a protein-protein interaction (PPI) network was built based on 122 VI-related DEGs. From the intersection of DEGs within the PPI and ceRNA networks, we obtained seven hub genes to build a novel prognostic risk score model. HCC patients with high-risk scores had shorter survival time and presented more advanced T/N/M stages as well as VI occurrence. In conclusion a novel prognostic model based on seven VI-associated DEGs within a circRNA-related ceRNA network was constructed in this study, with great ability to predict the outcome of HCC patients.

Patient Selection for Downstaging of Hepatocellular Carcinoma Prior to Liver Transplantation—Adjusting the Odds?

Background and Aims: Morphometric features such as the Milan criteria serve as standard criteria for liver transplantation (LT) in patients with hepatocellular carcinoma (HCC). Since it has been recognized that these criteria are too restrictive and do not adequately display the tumor biology, additional selection parameters are emerging.

Methods: Concise review of the current literature on patient selection for downstaging and LT for HCC outside the Milan criteria.

Results: The major task in patients outside the Milan criteria is the need for higher granularity with patient selection, since the benefit through LT is not uniform. The recent literature clearly shows that beneath tumor size and number, additional selection parameters are useful in the process of patient selection for and during downstaging. For initial patient selection, the alpha fetoprotein (AFP) level adds additional information to the size and number of HCC nodules concerning the chance of successful downstaging and LT. This effect is quantifiable using newer selection tools like the WE (West-Eastern) downstaging criteria or the Metroticket 2.0 criteria. Also an initial PET-scan and/or tumor biopsy can be helpful, especially in the high risk group of patients outside the University of California San Francisco (UCSF) criteria. After this entry selection, the clinical course during downstaging procedures concerning the tumor and the AFP response is of paramount importance and serves as an additional final selection tool.

Conclusion: Selection criteria for liver transplantation in HCC patients are becoming more and more sophisticated, but are still imperfect. The implementation of molecular knowledge will hopefully support a more specific risk prediction for HCC patients in the future, but do not provide a profound basis for clinical decision-making at present.

A novel prognostic model for hepatocellular carcinoma based on 5 microRNAs related to vascular invasion

BACKGROUND

Hepatocellular carcinoma (HCC) is prevalent worldwide with a high mortality rate. Prognosis prediction is crucial for improving HCC patient outcomes, but effective tools are still lacking. Characteristics related to vascular invasion (VI), an important process involved in HCC recurrence and metastasis, may provide ideas on prognosis prediction.

METHODS

Tools, including R 4.0.3, Funrich version 3, Cytoscape 3.8.2, STRING 11.5, Venny 2.1.0, and GEPIA 2, were used to perform bioinformatic analyses. The VI-related microRNAs (miRNAs) were identified using Gene Expression Omnibus HCC miRNA dataset GSE67140, containing 81 samples of HCC with VI and 91 samples of HCC without VI. After further evaluated the identified miRNAs based on The Cancer Genome Atlas database, a prognostic model was constructed via Cox regression analysis. The miRNAs in this model were also verified in HCC patients. Moreover, a nomogram was developed by integrating risk score from the prognostic model with clinicopathological parameters. Finally, a potential miRNA-mRNA network related to VI was established through weighted gene co-expression network analysis of HCC mRNA dataset GSE20017, containing 40 samples of HCC with VI and 95 samples of HCC without VI.

RESULTS

A prognostic model of 5 VI-related miRNAs (hsa-miR-126-3p, hsa-miR-148a-3p, hsa-miR-15a-5p, hsa-miR-30a-5p, hsa-miR-199a-5p) was constructed. The area under receiver operating characteristic curve was 0.709 in predicting 5-year survival rate, with a sensitivity of 0.74 and a specificity of 0.63. The nomogram containing risk score could also predict prognosis. Moreover, a VI-related miRNA-mRNA network covering 4 miRNAs and 15 mRNAs was established.

CONCLUSION

The prognostic model and nomogram might be potential tools in HCC management, and the VI-related miRNA-mRNA network gave insights into how VI was developed.

Bioinformatical identification of key genes regulated by IGF2BP2-mediated RNA N6-methyladenosine and prediction of prognosis in hepatocellular carcinoma

Background

The treatment of hepatocellular carcinoma (HCC), a malignant cancer with global spread, remains unsatisfactory, and novel prognostic biomarkers need to be identified. N6-methyladenosine (m⁶A) has been found to regulate tumor initiation and progression through different mechanisms. As a dynamic and reversible messenger RNA (mRNA) modification, m⁶A can be read by insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2). IGF2BP2 targets thousands of mRNA transcripts, which may be involved in HCC progression.

Methods

In this study, we integrated 4 classes of datasets including The Cancer Genome Atlas (TCGA)-LICH, m⁶A-sequencing data of HepG2 cells, and RNA-sequencing data of IGF2BP2-knockdown HepG2 cells to explore the key genes regulated by IGF2BP2-mediated m⁶A in HCC. The expression and m⁶A modification of candidates were validation in independent microarray expression profile of HCC tissue and annotated m⁶A database RMBase. The relationship of immune cell infiltration and the genes expression was estimated by CIBERSORT and TIMER.

Results

A total of 89 candidate genes were filtered. Next, cluster analysis was performed base on functions and pathways to identify the enrichment pathways. By constructing a protein-protein interaction (PPI) network, we found 54 nodes. Ten significant genes were filtered from the PPI. These genes were validated in data of an independent microarray and an m⁶A database. We found that the upregulation of these 10 genes was associated with poor prognosis. In addition, we showed the expression of these 10 genes was associated with the infiltration of variety of immune cell and tumor purity.

Conclusions

These identified genes may provide novel insights and facilitate the development of potential biomarkers for HCC diagnosis, as well as provide clues for IGF2BP2 inhibition therapy in HCC.

Circulating microRNAs: Biomarkers of disease

MicroRNAs are a class of endogenous noncoding single-stranded RNA molecules with approximately 20-24 nucleotides and are associated with a broad range of biological processes. Researchers found that microRNAs are abundant in tissues, and more importantly, there are also trace circulating microRNAs that exist in biological fluids. In recent years, circulating microRNAs had emerged as promising diagnostic and prognostic biomarkers for the noninvasive detection of diseases with high specificity and sensitivity. More importantly, specific microRNA expression signatures reflect not only the existence of early-stage diseases but also the dynamic development of advanced-stage diseases, disease prognosis prediction, and drug resistance. To date, an increasing number of potential miRNA biomarkers have been reported, but their practical application prospects are still unclear. Therefore, microRNAs, as potential diagnostic and prognostic biomarkers in a variety of diseases, need to be updated, as they are of great importance in the diagnosis, prognosis and prediction of therapeutic responses. In this review, we summary our current understanding of microRNAs as potential biomarkers in the major diseases (e.g., cancers and cardio-cerebrovascular diseases), which provide the basis for the design of diagnosis and treatment plan and the improvement of the cure rate.

Bioinformatic analysis and in vitro validation of a five-microRNA signature as a prognostic biomarker of hepatocellular carcinoma

Background

Existing research has identified correlations between numerous microRNAs (miRNAs) and the prognosis of hepatocellular carcinoma (HCC). However, the role of a combination of miRNAs in predicting HCC survival requires further elucidation.

Methods

miRNA expression profiles and clinical data from HCC patients were downloaded from The Cancer Genome Atlas (TCGA). Differentially expressed (DE) miRNAs in tumor versus normal samples were identified. All HCC patients were randomly assigned to a training cohort or a validation cohort at a ratio of 1 to 1. A least absolute shrinkage and selection operator (LASSO) Cox regression model was subsequently employed to establish the miRNA signature. The constructed miRNA signature was then developed and validated.

Results

In total, 127 DE miRNAs were detected between HCC and paracancerous tissue using HCC RNA sequencing (RNA-Seq) data extracted from TCGA database. LASSO Cox regression generated a five-miRNA signature consisting of has-mir-105-2, has-mir-9-3, has-mir-137, has-mir-548f-1, and has-mir-561 in the training cohort. This risk model was significantly related to survival (P=5.682e-6). Log-rank tests and multivariate Cox regression analyses revealed the five-miRNA signature as an independent prognostic indicator [HR =3.285, 95% confidence interval (CI): 1.737–6.213], with the area under curve (AUC) of the miRNA signature being 0.728. The effects of the miRNA signature were further confirmed in the validation cohort and in the OncomiR Cancer Database and Gene Expression Omnibus (GEO) dataset. Functional enrichment analysis revealed the potential effects of the five-miRNA signature in tumor-related biological pathways and processes. Cell Counting Kit-8, Transwell, and wound healing assays, were used to evaluate the role of has-mir-137 in HCC cell proliferation and migration in vitro.

Conclusions

We established a novel five-miRNA signature which reliably predicted prognosis in HCC patients and which could be used to assist in both strategic counseling and personalized management in HCC.

Definition of a novel vascular invasion-associated multi-gene signature for predicting survival in patients with hepatocellular carcinoma

The aim of the present study was to identify a vascular invasion-associated gene signature for predicting prognosis in patients with hepatocellular carcinoma (HCC). Using RNA-sequencing data of 292 HCC samples from The Cancer Genome Atlas (TCGA), the present study screened differentially expressed genes (DEGs) between patients with and without vascular invasion. Feature genes were selected from the DEGs by support vector machine (SVM)-based recursive feature elimination (RFE-SVM) algorithm to build a classifier. A multi-gene signature was selected by L1 penalized (LASSO) Cox proportional hazards (PH) regression model from the feature genes selected by the RFE-SVM to develop a prognostic scoring model. TCGA set was defined as the training set and was divided by the gene signature into a high-risk group and a low-risk group. Involvement of the DEGs between the two risk groups in pathways was also investigated. The presence and absence of vascular invasion between patients of training set was 175 DEGs. A classification model of 42 genes performed well in differentiating patients with and without vascular invasion on the training set and the validation set. A 14-gene prognostic model was built that could divide the training set or the validation set into two risk groups with significantly different survival outcomes. A total of 762 DEGs in the two risk groups of the training set were revealed to be significantly associated with a number of signaling pathways. The present study provided a 42-gene classifier for predicting vascular invasion, and identified a vascular invasion-associated 14-gene signature for predicting prognosis in patients with HCC. Several genes and pathways in HCC development are characterized and may be potential therapeutic targets for this type of cancer.

Significantly different expression levels of microRNAs associated with vascular invasion in hepatocellular carcinoma and their prognostic significance after surgical resection

BACKGROUND

Although gross vascular invasion (VI) has prognostic significance in patients with hepatocellular carcinoma (HCC) who have undergone hepatic resection, few studies have investigated the relationship between gross VI and aberrant expression of microribonucleic acids (miRNAs and miRs). Thus, the objective of this study was to identify miRNAs selectively expressed in HCC with gross VI and investigate their prognostic significance.

MATERIALS AND METHODS

Eligible two datasets (accession number: GSE20594 and GSE67140) were collected from the National Center for Biotechnology Information's (NCBI) Gene Expression Omnibus (GEO) database to compare miRNAs expression between HCC with and without gross VI. Differentially expressed miRNAs were externally validated using expression data from The Cancer Genome Atlas (TCGA) database. Prognostic significance and predicted functions of selected miRNAs for HCC were also investigated.

RESULTS

Thirty-five miRNAs were differentially expressed between HCC with and without gross VI in both datasets. Among them, three miRNAs were validated using TCGA database. miR-99a, miR-100, and miR-148a were downregulated to a greater extent in patients with HCC and gross VI than in those with HCC but no gross VI. Receiver operating characteristic (ROC) curve analysis showed discriminatory power of these miRNAs in predicting gross VI. Multivariate survival analysis revealed that types of surgery, advanced tumor node metastasis (TNM) stage, and low expression of miR-100-5p were independently associated with tumor recurrence. It also revealed that types of surgery, advanced TNM stage, low expression of miR-100-5p and miR-148a-3p were independent risk factors for overall survival (OS) after hepatic resection for HCC. A text mining analysis revealed that these miRNAs were linked to multifaceted hallmarks of cancer, including "invasion and metastasis."

CONCLUSIONS

Low expressions of miR-100-5p and miR-148a-3p were associated with gross VI and poor survival of patients after hepatic resection for HCC.

A seven-miRNA expression-based prognostic signature and its corresponding potential competing endogenous RNA network in early pancreatic cancer

The present study aimed to establish a microRNA (miRNA/miR) signature to predict the prognosis of patients with pancreatic cancer (PC) at the early stage and to investigate the involvement of competing endogenous RNAs (ceRNAs) in PC. Using mature miRNA expression profiles from The Cancer Genome Atlas, differentially expressed miRNAs in tissues derived from patients exhibiting early PC and tissues from healthy individuals were compared. The least absolute shrinkage and selection operator regression method was used to construct a miRNA-based signature for predicting prognosis. The miRNet tool, gene set enrichment analysis (GSEA) and the LncRNADisease database were utilized to explore the mechanistic involvement of ceRNAs. A total of seven downregulated miRNAs in PC (miR-424-5p, miR-139-5p, miR-5586-5p, miR-126-3p, miR-3613-5p, miR-454-3p and miR-1271-5p) were selected to generate a signature. Based on this seven-miRNA signature, it was possible to stratify patients with PC into low- and high-risk groups. The overall survival of the low-risk group was significantly longer than that of the high-risk group (P<0.001). The seven-miRNA signature was able to predict the 2-year-survival rate of patients with early PC with an area under the curve of 0.750. Furthermore, as opposed to routine clinicopathological features, this seven-miRNA signature was an independent prognostic factor according to multivariate Cox regression analysis. GSEA indicated that the extracellular matrix receptor interaction pathway and the transforming growth factor-β signaling pathway were enriched in the high-risk group. A ceRNA network of the seven-miR signature was constructed. In conclusion, the present study provided a seven-miRNA signature, according to which patients with early PC may be divided into high- and low-risk groups. The ceRNA network of the prognostic signature was preliminarily explored.

Long non-coding RNA expression profile can predict early recurrence in hepatocellular carcinoma after curative resection

AIM

The aim of this study was to develop a novel long non-coding RNA (lncRNA) expression signature to accurately predict early recurrence for patients with hepatocellular carcinoma (HCC) after curative resection.

METHODS

Using expression profiles downloaded from The Cancer Genome Atlas database, we identified multiple lncRNAs with differential expression between early recurrence (ER) and non-early recurrence (non-ER) groups of patients with HCC. Least absolute shrinkage and selection operator for logistic regression models were used to develop an lncRNA-based classifier for predicting ER in the training set. An independent test set was used to validate the predictive value of this classifier. Furthermore, a co-expression network based on these lncRNAs and its highly related genes was constructed and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of genes in the network were carried out.

RESULTS

We identified 10 differentially expressed lncRNAs, including three that were upregulated and seven that were downregulated in the ER group. The lncRNA-based classifier was constructed based on seven lncRNAs (AL035661.1, PART1, AC011632.1, AC109588.1, AL365361.1, LINC00861, and LINC02084), and its accuracy was 0.83 in the training set, 0.87 in the test set, and 0.84 in the total set. Receiver operating characteristic curve analysis showed the area under the curve was 0.741 in the training set, 0.824 in the test set, and 0.765 in the total set. A functional enrichment analysis suggested that the genes highly related to four lncRNAs are involved in the immune system.

CONCLUSION

The expression profile of seven lncRNAs can effectively predict ER after surgical resection for HCC.

Role of microRNAs in the main molecular pathways of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver malignant neoplasia. HCC is characterized by a poor prognosis. The need to find new molecular markers for its diagnosis and prognosis has led to a progressive increase in the number of scientific studies on this topic. MicroRNAs (miRNAs) are small non-coding RNA that play a role in almost all main cellular pathways. miRNAs are involved in the regulation of expression of the major tumor-related genes in carcinogenesis, acting as oncogenes or tumor suppressor genes. The aim of this review was to identify papers published in 2017 investigating the role of miRNAs in HCC tumorigenesis. miRNAs were classified according to their role in the main molecular pathways involved in HCC tumorigenesis: (1) mTOR; (2) Wnt; (3) JAK/STAT; (4) apoptosis; and (5) MAPK. The role of miRNAs in prognosis/response prediction was taken into consideration. Bearing in mind that the analysis of miRNAs in serum and other body fluids would be crucial for clinical management, the role of circulating miRNAs in HCC patients was also investigated. The most represented miRNA-regulated pathway in HCC is mTOR, but apoptosis, Wnt, JAK/STAT or MAPK pathways are also influenced by miRNA expression levels. These miRNAs could thus be used in clinical practice as diagnostic, prognostic or therapeutic targets for HCC treatment.