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

MicroRNAs and their vital role in apoptosis in hepatocellular carcinoma: miRNA-based diagnostic and treatment methods

Hepatocellular carcinoma (HCC) is one of the most prevalent malignancies with high invasive and metastatic capability. Although significant advances have been made in the treatment of HCC, the overall survival rate of patients is still low. It is essential to explore accurate biomarkers for early diagnosis and prognosis along with therapeutic procedures to increase the survival rate of these patients. Anticancer therapies can contribute to induce apoptosis for the elimination of cancerous cells. However, dysregulated apoptosis and proliferation signaling pathways lead to treatment resistance, a significant challenge in improving efficient therapies. MiRNAs, short non-coding RNAs, play crucial roles in the progression of HCC, which regulate gene expression through post-transcriptional inhibition and targeting mRNA degradation in cancers. Dysregulated expression of multiple miRNAs is associated with numerous biological processes, including cell proliferation, apoptosis, invasion and metastasis, epithelial-mesenchymal transition (EMT), angiogenesis, and drug resistance in HCC. This review summarizes the role and potential efficacy of miRNAs in promoting and inhibiting cell proliferation and apoptosis in HCC, as well as the role of miRNAs in therapy resistance in HCC.

MicroRNA-154-5p suppresses cervical carcinoma growth and metastasis by silencing Cullin2 in vitro and in vivo

Background

MicroRNA-154-5p (miR-154-5p) plays a role in tumorigenesis in diverse human malignancies. Nevertheless, little is known about the mechanism by which miR-154-5p alters the growth and metastasis of cervical cancer. This research aimed to analyze the role of miR-154-5p in the pathology of cervical cancer in vitro and in vivo.

Methods

The level of miR-154-5p in human papillomavirus 16 positive cervical cancer cells was examined by real-time quantitative polymerase chain reaction. Bioinformatics predicted the downstream targets and potential functions of miR-154-5p. Furthermore, lentiviral technology was used to construct SiHa cell lines with stable up- and down-expression levels of miR-154-5p. Its differential expression effects on the progress and metastasis of cervical cancer were analyzed using cell culture and animal models.

Results

MiR-154-5p showed low expression in cervical cancer cells. Overexpression of miR-154-5p could markedly inhibit the proliferation, migration, and colony formation ability of SiHa cells, concomitantly leading to G1 arrest of the cell cycle, while silencing miR-154-5p triggered the opposite results. Meanwhile, overexpression of miR-154-5p restrained the growth and metastasis of cervical cancer by silencing CUL2 in vivo. Additionally, miR-154-5p reduced CUL2 level, and overexpression of CUL2 influenced the effect of miR-154-5p in cervical cancer. In conclusion, miR-154-5p restrained the growth and metastasis of cervical cancer by directly silencing CUL2.

Diagnostic Significance of hsa-miR-21-5p, hsa-miR-192-5p, hsa-miR-155-5p, hsa-miR-199a-5p Panel and Ratios in Hepatocellular Carcinoma on Top of Liver Cirrhosis in HCV-Infected Patients

Early hepatocellular carcinoma (HCC) diagnosis is challenging. Moreover, for patients with alpha-fetoprotein (AFP)-negative HCC, this challenge is augmented. MicroRNAs (miRs) profiles may serve as potential HCC molecular markers. We aimed to assess plasma homo sapiens-(hsa)-miR-21-5p, hsa-miR-155-5p, hsa-miR-192-5p, and hsa-miR-199a-5p-expression levels as a panel of biomarkers for HCC in chronic hepatitis C virus (CHCV) patients with liver cirrhosis (LC), especially AFP-negative HCC cases, as a step toward non-protein coding (nc) RNA precision medicine.

SUBJECTS AND METHODS

79 patients enrolled with CHCV infection with LC, subclassified into an LC group without HCC (n = 40) and LC with HCC (n = 39). Real-time quantitative PCR was used to measure plasma hsa-miR-21-5p, hsa-miR-155-5p, hsa-miR-192-5p, and hsa-miR-199a-5p.

RESULTS

Plasma hsa-miR-21-5p and hsa-miR-155-5p demonstrated significant upregulation, while hsa-miR-199a-5p demonstrated significant downregulation in the HCC group (n = 39) when compared to the LC group (n = 40). hsa-miR-21-5p expression was positively correlated with serum AFP, insulin, and insulin resistance (r = 0.5, p < 0.001, r = 0.334, p = 0.01, and r = 0.303, p = 0.02, respectively). According to the ROC curves, for differentiating HCC from LC, combining AFP with each of hsa-miR-21-5p, hsa-miR-155-5p, and miR199a-5p improved the diagnostic sensitivity to 87%, 82%, and 84%, respectively, vs. 69% for AFP alone, with acceptable specificities of 77.5%, 77.5%, and 80%, respectively, and AUC = 0.89, 0.85, and 0.90, respectively vs. 0.85 for AFP alone. hsa-miR-21-5p/hsa-miR-199a-5p and hsa-miR-155-5p/hsa-miR-199a-5p ratios discriminated HCC from LC at AUC = 0.76 and 0.71, respectively, with sensitivities = 94% and 92% and specificities = 48% and 53%, respectively. Upregulation of plasma hsa-miR-21-5p was considered as an independent risk factor for HCC development [OR = 1.198(1.063-1.329), p = 0.002].

CONCLUSIONS

Combining each of hsa-miR-21-5p, hsa-miR-155-5p, and hsa-miR-199a-5p with AFP made it possible to identify HCC development in the LC patients' cohort with higher sensitivity than using AFP alone. hsa-miR-21-5p/hsa-miR-199a-5p and hsa-miR-155-5p/hsa-miR-199a-5p ratios are potential HCC molecular markers for AFP-negative HCC patients. hsa-miR-21-5p was linked, clinically and via in silico proof, to insulin metabolism, inflammation, dyslipidemia, and tumorigenesis in the HCC patients' group as well as for an upregulated independent risk factor for the emergence of HCC from LC in the CHCV patients.

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.

Identification of a novel ceRNA network related to prognosis and immunity in HNSCC based on integrated bioinformatic investigation

Head and neck squamous cell carcinoma (HNSCC) is characterized by an immunosuppression environment and necessitates the development of new immunotherapy response predictors. The study aimed to build a prognosis-related competing endogenous RNA (ceRNA) network based on immune-related genes (IRGs) and analyze its immunological signatures. Differentially expressed IRGs were identified by bioinformatics analysis with Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and ImmPort databases. Finally, via upstream prognosis-related microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) prediction and co-expression analysis, we built an immune-related ceRNA network (LINC00052/hsa-miR-148a-3p/PLAU) related to HNSCC patient prognosis. CIBERSORT analysis demonstrated that there were substantial differences in 11 infiltrating immune cells in HNSCC, and PLAU was closely correlated with 10 type cells, including T cells CD8+ (R =  - 0.329), T cells follicular helper (R = - 0.342) and macrophage M0 (R = 0.278). Methylation and Tumor Immune Dysfunction and Exclusion (TIDE) analyses revealed that PLAU upregulation was most likely caused by hypomethylation and that high PLAU expression may be associated with tumor immune evasion in HNSCC, respectively.

A Bioinformatic Approach Based on Systems Biology to Determine the Effects of SARS-CoV-2 Infection in Patients with Hypertrophic Cardiomyopathy

Recently, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), has infected millions of individuals worldwide. While COVID-19 generally affects the lungs, it also damages other organs, including those of the cardiovascular system. Hypertrophic cardiomyopathy (HCM) is a common genetic cardiovascular disorder. Studies have shown that HCM patients with COVID-19 have a higher mortality rate; however, the reason for this phenomenon is not yet elucidated. Herein, we conducted transcriptomic analyses to identify shared biomarkers between HCM and COVID-19 to bridge this knowledge gap. Differentially expressed genes (DEGs) were obtained using the Gene Expression Omnibus ribonucleic acid (RNA) sequencing datasets, GSE147507 and GSE89714, to identify shared pathways and potential drug candidates. We discovered 30 DEGs that were common between these two datasets. Using a combination of statistical and biological tools, protein-protein interactions were constructed in response to these findings to support hub genes and modules. We discovered that HCM is linked to COVID-19 progression based on a functional analysis under ontology terms. Based on the DEGs identified from the datasets, a coregulatory network of transcription factors, genes, proteins, and microRNAs was also discovered. Lastly, our research suggests that the potential drugs we identified might be helpful for COVID-19 therapy.