A novel microRNA signature predicts survival in liver hepatocellular carcinoma after hepatectomy

Propofol regulates the progression of hepatocellular carcinoma via the POLR2L/TGF-β signaling pathway

Background

Hepatocellular carcinoma (HCC) is a malignant tumor with high morbidity and mortality. Propofol has been reported to modulate tumorigenesis in HCC; the aim of this study was to investigate the effect of the interaction of propofol with POLR2L on HCC tumor progression in HCC.

Methods

The propofol-related GSE101724 dataset was analyzed using weighted gene co-expression network analysis (WGCNA) and differentially expressed genes (DEGs) to identify overlapping genes. Key genes were selected from The Cancer Genome Atlas-liver hepatocellular carcinoma (TCGA-LIHC)-DEGs for prognostic analysis. The impact of POLR2L on LIHC patient survival was assessed, followed by in vitro experiments to validated its effects on HCC cell behavior and signaling pathways.

Results

Fourteen overlapping genes were identified in the turquoise module (highest correlation) of up-regulated DEGs and GSE101724. Further analysis obtained 11 key overlapping genes from 14 overlapping genes and TCGA-LIHC-DEGs, among which HSPE1 and POLR2L showed significant prognostic correlation. Patients with LIHC have a worse chance of surviving when their POLR2L expression is elevated. Knockdown POLR2L significantly inhibited the proliferation, invasion, and migration of HCC cell lines. Downregulation of POLR2L was accompanied by induced apoptosis, cell cycle arrest, and modulation of the expression of apoptosis-related genes. Propofol was found to downregulate POLR2L expression, inhibiting cell proliferation and growth. Further, it was shown that propofol controlled the development of HCC by influencing the POLR2L/TGF-β signaling loop.

Conclusions

The results validated the predictive relevance of POLR2L in HCC and emphasized that propofol can regulate HCC progression through the POLR2L/TGF-β signaling pathway.

HOMER3 promotes liver hepatocellular carcinoma cancer progression by -upregulating EZH2 and mediating miR-361/GPNMB axis

Liver hepatocellular carcinoma (LIHC) is among the most lethal human cancers. Studies have shown that Homer scaffold protein 3 (HOMER3) plays important roles in various diseases and cancers, but its biological function and molecular mechanism in LIHC have never been investigated. Our study discovered the aberrantly high expression of HOMER3 and its promising diagnostic and prognostic significance in LIHC. Functionally, HOMER3 knockdown inhibited the proliferative and migrative abilities of LIHC cells and tumor growth in vivo. Mechanically, HOMER3 mediated the aggressiveness of LIHC cells via GPNMB. Meanwhile, miR-361 directly targeted GPNMB and attenuated LIHC progression by suppressing GPNMB expression. The regulatory effect of HOMER3 during LIHC progression was exerted through the miR-361/GPNMB axis. Furthermore, EZH2 supplementation or miR-361 depletion effectively abated the tumor-suppressive effect of HOMER3 knockdown on LIHC progression. In conclusion, HOMER3 mediated LIHC progression through the EZH2/miR-361/GPNMB axis.

A nomogram based on 4-lncRNAs signature for improving prognostic prediction of hepatocellular carcinoma

PURPOSE

Long noncoding RNAs (lncRNAs) with abnormal expression are frequently seen in hepatocellular cancer patients (HCC). Previous studies have reported the correlation between lncRNA and prognosis processes of HCC patients. In this research, a graphical nomogram with lncRNAs signatures, T, M phases was developed using the rms R package to estimate the survival rates of HCC patients in year 1, 3, and 5.

METHODS

To find the prognostic lncRNA and create the lncRNA signatures, univariate Cox survival analysis and multivariate Cox regression analysis were chosen. The rms R software package was used to build a graphical nomogram based on lncRNAs signatures to predict the survival rates in of HCC patients in 1, 3, and 5 years. Using "edgeR", "DEseq" R packages to find the differentially expressed genes (DEGs).

RESULTS

Firstly, a total of 5581 DEGs including 1526 lncRNAs and 3109 mRNAs were identified through bioinformatic analysis, of which 4 lncRNAs (LINC00578, RP11-298O21.2, RP11-383H13.1, RP11-440G9.1) were identified to be strongly related to the prognosis of liver cancer (P < 0.05). Moreover, we constructed a 4-lncRNAs signature by using the calculated regression coefficient. 4-lncRNAs signature is identified to significantly correlated with clinical and pathological characteristics (such as T stage, and death status of HCC patients).

CONCLUSIONS

A prognostic nomogram on the base of 4-lncRNAs markers was built, which is capable to accurately predict the 1-year, 3-year, and 5-year survival of HCC patients after the construction of the 4-lncRNAs signature linked with prognosis of HCC.

A PTEN-Autophagy Risk Model for the Prediction of Prognosis and Immune Microenvironment in Hepatocellular Carcinoma

Background

The clinical behavior and molecular mechanisms of hepatocellular carcinoma (HCC) are complex and highly variable, limiting the discovery of new targets and therapies in clinical research. Phosphatase and tensin homolog deleted on chromosome 10 (PTEN) is one of the tumor suppressor genes. It is of great interest to discover the role of unexplored correlation among PTEN, the tumor immune microenvironment, and autophagy-related signaling pathways and to construct a reliable risk model for prognosis during HCC progression.

Method

We first performed differential expression analysis on the HCC samples. By using Cox regression and LASSO analysis, we determined the DEGs contributing to the survival benefit. In addition, the gene set enrichment analysis (GSEA) was performed to identify potential molecular signaling pathways regulated by the PTEN gene signature, autophagy, and autophagy-related pathways. ESTIMATE was also employed for evaluating the composition of immune cell populations.

Results

We found a significant correlation between PTEN expression and the tumor immune microenvironment. The low-PTEN expression group had higher immune infiltration and lower expression of immune checkpoints. In addition, PTEN expression was found to be positively correlated with autophagy-related pathways. Then, differentially expressed genes between tumor and tumor-adjacent samples were screened, and 2895 genes were significantly associated with both PTEN and autophagy. Based on PTEN-related genes, we identified 5 key prognostic genes, including BFSP1, PPAT, EIF5B, ASF1A, and GNA14. The 5-gene PTEN-autophagy risk score (RS) model was demonstrated to have favorable performance in the prediction of prognosis.

Conclusion

In summary, our study showed the importance of the PTEN gene and its correlation with immunity and autophagy in HCC. The PTEN-autophagy.RS model we established could be used to predict the prognosis of HCC patients and showed significantly higher prognostic accuracy than the TIDE score in response to immunotherapy.

Expression and prognostic potential of TMEM204: a pan-cancer analysis

TMEM204 (Transmembrane Protein 204) is a member of the TMEM family that regulates cell function and angiogenesis. Previous studies showed that TMEM204 is related to pancreatic cancer, but its roles in other cancers remain unknown. To reveal this relationship, we conducted a pan-cancer analysis by several online databases. The expression of TMEM204 was analyzed by Oncomine and Tumor Immune Estimation Resource2.0 (TIMER2.0). The prognostic potential of TMEM204 was evaluated by the GEPIA2, UALCAN, and Oncolnc. The methylation level of gene expression was analyzed by UALCAN, and the relationship between cancer and immune invasion was displayed by TIMER2.0. The Protein-Protein Interactions Network and functional analysis of TMEM204 and its related genes were conducted by STRING and Webgestalt. We found that TMEM204 expression was up-regulated and correlated with prognosis in multiple cancers. In liver hepatocellular carcinoma (LIHC), high TMEM204 expression was associated with a good prognosis, and with high infiltrating levels of CD8⁺ T and CD4⁺ T cells, macrophages, neutrophils, and myeloid dendritic cells. In addition, the methylation level in LIHC was higher than in normal tissues. p53 signaling pathway and Fanconi anemia pathway were implicated by KEGG pathway analysis. These results indicate that TMEM204 is associated with the prognosis, methylation, and immune invasion of cancers, especially LIHC. TMEM204 may act as a prognostic marker of LIHC and its role in other cancers should be studied.

LRP1B mutation associates with increased tumor mutation burden and inferior prognosis in liver hepatocellular carcinoma

BACKGROUND

Liver hepatocellular carcinoma (LIHC) is the most common primary liver cancer and the main cause of death in patients with cirrhosis. LRP1B is found to involve in a variety of cancers, but the association of LRP1B mutation with tumor mutation burden (TMB) and prognosis of LIHC is rarely studied.

METHODS AND RESULTS

Herein, we analyzed the somatic mutation data of 364 LIHC patients from The Cancer Genome Atlas (TCGA) and found that LRP1B showed elevated mutation rate. Calculation of the TMB in LRP1B mutant and LRP1B wild-type groups showed that LRP1B mutant group had higher TMB compared with that in LRP1B wild-type group. Then survival analysis was performed and the survival curve showed that LRP1B mutation was associated with poor survival outcome, and this association remained to be significant after adjusting for multiple confounding factors including age, gender, tumor stage, mutations of BRCA1, BRCA2, and POLE.

CONCLUSION

Collectively, our results revealed that LRP1B mutation was related to high TMB value and poor prognosis in LIHC, indicating that LRP1B mutation is probably helpful for the selection of immunotherapy and prognosis prediction in LIHC.

miR-16 Inhibits Extracellular Signal-Regulated Kinases (ERK) Mitogen-Activated Protein Kinases (MAPK) Signaling to Affect Epithelial-Mesenchymal Transition (EMT) and Invasion of Glioma Cells

Abnormal MEK1 expression is associated with tumor cell EMT, invasion and metastasis. Decreased miR-16 level is associated with glioma. Bioinformatics analysis showed a relationship between miR-16 and MEK1. This study assessed whether miR-16 regulates MEK1 expression and affects glioma cell EMT and invasion. The tumor tissues and adjacent glioma tissues were collected to measure miR-16 and MEK1 mRNA. The dual luciferase assay validated the relation of miR-16 with MEK1. U251 cells were cultured and assigned into NC group and mimic group, followed by analysis of cell biological behaviors, and MEK1, p-ERK1/2, E-cadherin, N-Cadherin expression. Compared with adjacent tissues, miR-16 expression was significantly decreased and MEK1 was elevated in glioma tissues. Compared with HEB, miR-16 in glioma U251 and SHG44 cells was decreased and MEK1 was increased. Dual luciferase reporter gene experiments confirmed the relation of miR-16 with MEK1. Transfection of miR-16 mimic significantly down-regulated MEK1, p-ERK1/2 and N-cadherin in U251 cells, upregulated E-cadherin, inhibited cell proliferation, promoted apoptosis, and attenuated EMT and invasion of glioma cells. In conclusion, decreased miR-16 expression and increased MEK1 expression is related to glioma pathogenesis. Overexpression of miR-16 can inhibit MEK1 expression, ERK/MAPK signaling, glioma cell proliferation, promote apoptosis, and attenuate EMT and invasion.

Construction of an HCC recurrence model based on the investigation of immune-related lncRNAs and related mechanisms

Long noncoding RNAs (lncRNAs) are emerging as critical regulators of gene expression and play fundamental roles in immune regulation. Growing evidence suggests that immune-related genes and lncRNAs can serve as markers to predict the prognosis of patients with cancers, including hepatocellular carcinoma (HCC). This study aimed to contract an immune-related lncRNA (IR-lncRNA) signature for prospective assessment to predict early recurrence of HCC. A total of 319 HCC samples under radical resection were randomly divided into a training cohort (161 samples) and a testing cohort (158 samples). In the training dataset, univariate, lasso, and multivariate Cox regression analyses identified a 9-IR-lncRNA signature closely related to disease-free survival. Kaplan-Meier analysis, principal component analysis, gene set enrichment analysis, and nomogram were used to evaluate the risk model. The results were further confirmed in the testing cohort. Furthermore, we constructed a competitive endogenous RNA regulatory network. The results of the present study indicated that this 9-IR-lncRNA signature has important clinical implications for improving predictive outcomes and guiding individualized treatment in HCC patients. These IR-lncRNAs and regulated genes may be potential biomarkers associated with the prognosis of HCC.

Molecular classification of hepatocellular carcinoma: prognostic importance and clinical applications

Hepatocellular carcinoma (HCC) is a lethal human malignancy with a very low overall and long-term survival rate. Poor prognostic outcomes are predominantly associated with HCC due to a huge landscape of heterogeneity found in the deadliest disease. However, molecular subtyping of HCC has significantly improved the knowledge of the underlying mechanisms that contribute towards the heterogeneity and progression of the disease. In this review, we have extensively summarized the current information available about molecular classification of HCC. This review can be of great significance for providing the insight information needed for development of novel, efficient and personalized therapeutic options for the treatment of HCC patients globally.

Construction and validation of a three-microRNA signature as prognostic biomarker in patients with hepatocellular carcinoma

Hepatocellular carcinoma (HCC), a common type of primary liver cancer, is one of the most aggressive malignant tumors worldwide. Although overall survival (OS) rates for HCC has significantly improved in recent years, however, the exact predictive value of microRNA (miRNA) for the prognosis of HCC has not yet been recognized. Here, we aimed to identify potential prognostic miRNAs involved in HCC by bioinformatics analysis and validated expression levels through quantitative polymerase chain reaction (qPCR) and GEO database. The RNA expression profiles and corresponding clinical information of HCC were available from The Cancer Genome Atlas (TCGA) datasets. Differentially expression and standardization analysis of miRNAs, Kaplan-Meier curve and time dependent ROC curve were performed by using R tools. Differentially expressed miRNAs (DEmiRNAs) and clinical parameters involved in the OS of HCC were confirmed by Cox regression models. And functional enrichment analysis was used to establish functions of the targeted genes of DEmiRNAs. A total of 300 DEmiRNAs were significantly related with HCC, of which 40 were down-regulated and 260 were up-regulated. A total of 344 patients with DEmiRNAs, status, overall survival (OS) time were randomized into training group (172) and test group (172). Multivariate Cox regression analyses revealed that 3 miRNA (hsa-miR-139-3p, hsa-miR-760, hsa-miR-7-5p) had independent prognostic significance for the OS of HCC in both training and test group. Moreover, according to Kaplan Meier analysis, the OS of HCC patients with high-risk score was shorter in validation and entire series. The time dependent ROC curve demonstrated high accuracy of the signature for OS. Besides, target genes of three miRNAs were analyzed by functional enrichment analysis and 20 genes associated with OS were verified by using Kaplan-Meier method. Compared with normal and benign group, the relative expression level of hsa-miR-139-3p was significantly decreased, while hsa-miR-7-5p and hsa-miR-760 were distinctly increased in the plasma of HCC patients. The same results were observed in the independent cohort. Collectively, our research suggested that three-miRNA signature could serve as an independent prognostic indicator for HCC patients.

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.

Identification of SARS-CoV-2 Proteins Binding Human mRNAs As a Novel Signature Predicting Overall Survival in Hepatocellular Carcinoma

The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the virus causing coronavirus disease 2019 (COVID-19), has been confirmed in cancers through binding specific mRNAs to invade human cells. Therefore, the aim of this study described here was to develop and validate novel SARS-CoV-2 proteins binding human mRNAs (SPBRs) signature to predict overall survival (OS) in hepatocellular carcinoma (HCC). Using multivariate Cox regression analysis, a set of SPBRs was identified to establish a multigene signature in the Cancer Genome Atlas repositories cohort. Furthermore, a nomogram was established based on the signature and clinical risk factors to improve risk stratification for individual patients. External validation was performed in the International Cancer Genome Consortium (ICGC) cohort. A six-SPBR signature was built to classify patients into two risk groups using a risk score with different OS in two cohorts (all p < 0.0001). Multivariate regression analysis demonstrated the signature was an independent predictor of HCC. Moreover, the signature presented an excellent diagnostic power in differentiating HCC and normal tissues. Gene set enrichment analysis demonstrated that high-risk group was closely enriched in cell cycle, DNA replication, microRNAs in cancer, and cytokine-cytokine receptor interaction. The novel signature demonstrated great clinical value in predicting the OS for patients with HCC, and will provide a good reference between cancer research and SARS-CoV-2 and help individualized treatment in HCC.

Biomarkers for hepatocellular cancer

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths worldwide. If diagnosed early, curative treatment options such as surgical resection, loco-regional therapies, and liver transplantation are available to patients, increasing their chances of survival and improving their quality of life. Unfortunately, most patients are diagnosed with late stage HCC where only palliative treatment is available. Therefore, biomarkers which could detect HCC early with a high degree of sensitivity and specificity, may play a crucial role in the diagnosis and management of the disease. This review will aim to provide an overview of the different biomarkers of HCC comprising those used in the diagnosis of HCC in at risk populations, as well as others with potential for prognosis, risk predisposition and prediction of response to therapeutic intervention.

A Five-Gene Signature Based on Stromal/Immune Scores in the Tumor Microenvironment and Its Clinical Implications for Liver Cancer

Increasing evidence highlights the clinical significance of stromal cells and immune cells in the liver cancer microenvironment. However, reliable prognostic models have not been well established. This study aimed to develop a gene signature for liver cancer based on stromal and immune scores. Using the estimation of stromal and immune cells in malignant tumor tissues using expression data (ESTIMATE) algorithm, stromal and immune scores were estimated based on the transcriptome profile of The Cancer Genome Atlas (TCGA) liver cancer cohort. Stromal-/immune-related differentially expressed genes were identified, followed by functional enrichment analysis. The Cox regression model was used to select prognostic genes and construct a gene signature. Its predictive potential was evaluated by receiver operating characteristic (ROC). The correlation between the risk score and immune cell infiltration was analyzed using Tumor Immune Estimation Resource (TIMER). Three hundred sixty-four upregulated and 10 downregulated stromal-/immune-related genes were identified, were mainly enriched in immune-related processes and pathways. Through univariate and multivariate cox survival analysis, a five-gene risk score was constructed, composed of FABP3, HTRA3, OLFML2B, PDZD4 and SLAMF6. Patients with high score indicated a poorer prognosis than those with low risk score. The areas under the ROC curves of overall survival (OS), progression-free interval, 3-, 5-year, OS status were 0.68, 0.57, 0.72, 0.74 and 0.728, indicating its well performance on predicting patients' prognoses. Furthermore, the risk score and the five genes were significantly correlated with immune cell infiltration in the tumor microenvironment. In this study, we proposed a prognostic five-gene signature based on stromal/immune scores in the liver cancer microenvironment.

Profiling of mRNA of interstitial fibrosis and tubular atrophy with subclinical inflammation in recipients after kidney transplantation

Interstitial fibrosis and tubular atrophy (IFTA) with inflammation (IFTA-I) is strongly correlated with kidney allograft failure. Diagnosis of IFTA-I accurately and early is critical to prevent graft failure and improve graft survival. In the current study, through analyzing the renal allograft biopsy in patients with stable function after kidney transplantation (STA), IFTA and IFTA-I group with semi-supervised principal components methods, we found that CD2, IL7R, CCL5 based signature could not only distinguish STA and IFTA-I well, but predict IFTA-I with a high degree of accuracy with an area under the curve (AUC) of 0.91 (P = 0.00023). Additionally, IRF8 demonstrated significant differences among STA, IFTA and IFTA-I groups, suggesting that IRF8 had the capacity to discriminate the different classifications of graft biopsies well. Also, with Kaplan-Meier and log-rank methods, we found that IRF8 could serve as the prognostic marker for renal graft failure in those biopsies without rejection (AUC = 0.75) and the recipients expressing high had a higher risk for renal graft loss (P < 0.0001). This research may provide new targets for therapeutic prevention and intervention for post-transplantation IFTA with or with inflammation.

Role of cellular, molecular and tumor microenvironment in hepatocellular carcinoma: Possible targets and future directions in the regorafenib era

Hepatocellular carcinoma (HCC) remains as one of the major causes of cancer-related mortality, despite the recent development of new therapeutic options. Regorafenib, an oral multikinase inhibitor, is the first systemic therapy that has a survival benefit for patients with advanced HCC that have a poor response to sorafenib. Even though regorafenib has been approved by the FDA, the clinical trial for regorafenib treatment does not show significant improvement in overall survival. The impaired efficacy of regorafenib caused by various resistance mechanisms, including epithelial-mesenchymal transitions, inflammation, angiogenesis, hypoxia, oxidative stress, fibrosis and autophagy, still needs to be resolved. In this review, we provide insight on regorafenib microenvironmental, molecular and cellular mechanisms and interactions in HCC treatment. The aim of this review is to help physicians select patients that would obtain the maximal benefits from regorafenib in HCC therapy.

Three-microRNA expression signature predicts survival in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a specific type of breast cancer with poor overall survival (OS) time. Previous studies revealed that microRNAs (miRNAs/miRs) serve important roles in the pathogenesis, progression and prognosis of TNBC. The present study analyzed the miRNA expression and clinical data of patients with TNBC downloaded from The Cancer Genome Atlas. A total of 194 differentially expressed miRNAs were identified between TNBC and matched normal tissues using the cut-off criteria of P<0.05 and |log2 fold change|>2. Of these miRNAs, 65 were downregulated and 129 were upregulated. Using Kaplan-Meier survival analysis, a total of 77 miRNAs that were closely associated with OS time were identified (P<0.05). The intersection of the 77 miRNAs and 194 differentially expressed miRNAs revealed six miRNAs. Log-rank tests based on survival curves were performed and two miRNAs were eliminated. The prognostic value of the remaining four miRNAs was evaluated with a Cox proportional hazards model using multiple logistic regression with forward stepwise selection of variables. Three miRNAs (miR-21-3p, miR-659-5p and miR-200b-5p) were subsequently identified as independent risk factors associated with OS time in the model. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses revealed that the target genes of these three miRNAs were mainly involved in ‘cell protein metabolism’, ‘RNA transcriptional regulation’, ‘cell migration’, ‘MAPK signaling pathway’, ‘ErbB signaling pathway’, ‘prolactin signaling pathway’ and ‘adherens junctions’. Taken together, the results obtained in the present study suggested that the three-miRNA signature may serve as a prognostic biomarker for patients with TNBC.

MiR-181a Promotes Apoptosis and Reduces Cisplatin Resistance by Inhibiting Osteopontin in Cervical Cancer Cells

Objective: In this study, the authors established a cervical cancer cisplatin (DDP) drug-resistant cell line to explore the role of miR-181a in the regulation of osteopontin (OPN) expression and the proliferation, apoptosis, as well as DDP resistance of cervical cancer cells. Materials and Methods: Dual luciferase reporter gene assay was performed to validate the targeted relationship between miR-181a and OPN. The DDP-resistant cell line CaSki/DDP was established to compare the expressions of miR-181a and OPN. The cell proliferation activity was detected by CCK-8 assay. CaSki/DDP cells were divided into miR-NC group and miR-181a mimic group followed by analysis of cell apoptosis by flow cytometry, and the cell proliferation by EdU staining. Results: There was a targeted relationship between miR-181a and OPN mRNA. MiR-181a expression was significantly lower, while OPN mRNA and protein levels were significantly higher in CaSki/DDP cells than that in CaSki cells. Compared with the miR-NC group, OPN mRNA and protein were significantly decreased, cell apoptosis was significantly increased, and cell proliferation ability was significantly attenuated in miR-181a mimic transfection group. Conclusions: The decrease of miR-181a expression and the upregulation of OPN expression are related to the DDP resistance of cervical cancer cells. Overexpression of miR-181a can inhibit the expression of OPN, induce cell apoptosis cells, restrain cell proliferation, and reduce DDP resistance in cervical cancer cells.

The role of miRNAs as biomarkers in prostate cancer

There is an urged need of non-invasive biomarkers for the implementation of precision medicine. These biomarkers are required to these days for improving prostate cancer (PCa) screening, treatment or stratification in current clinical strategies. There are several commercial kits (Oncotype DX genomic prostate score^®, Prolaris^®, among others) that use genomic changes, rearrangement or even non-coding RNA events. However, none of them are currently used in the routine clinical practice. Many recent studies indicate that miRNAs are relevant molecules (small single-stranded non-coding RNAs that regulate gene expression of more than 30% of human genes) to be implement non-invasive biomarkers. However, contrasting to others tumors, such as breast cancer where miR-21 seems to be consistently upregulated; PCa data are controversial. Here we reported an extended revision about the role of miRNAs in PCa including data of AR signaling, cell cycle, EMT process, CSCs regulation and even the role of miRNAs as PCa diagnostic, prognostic and predictive tool. It is known that current biomedical research uses big-data analysis like Next Generation Sequencing (NGS) analysis. We also conducted an extensive online search, including the main platforms and kits for miRNAs massive analysis (like MiSeq, Nextseq 550, or Ion S5™ systems) indicating their pros, cons and including pre-analytical and analytical issues of miRNA studies.

miR-424-5p Regulates Hepatoma Cell Proliferation and Apoptosis

OBJECTIVE

Yes-associated protein (Yes-associated protein 1 [YAP1]) is an important oncogene that is related to the pathogenesis and progression of liver cancer. It was found that miR-424-5p expression was significantly decreased in liver cancer tissues, revealing its anticancer effect. Bioinformatic analysis demonstrated the targeted relationship between miR-424-5p and the 3' untranslated region of YAP1. This study investigated the role of miR-424-5p in regulating YAP1 expression and affecting hepatoma cell proliferation and apoptosis.

MATERIALS AND METHODS

Tumors and normal liver tissues adjacent to tumors were collected from patients to detect the expression of miR-424-5p and YAP1. A dual-luciferase reporter gene assay was adopted to explore the targeted regulation between miR-424-5p and YAP1. Liver cancer HCCLM3 and MHCC97-L cells and normal liver HL-7702 cells were cultured in vitro to compare expression levels of miR-424-5p and YAP1. HCCLM3 and MHCC97-L cells were divided into the miR-NC group and miR-424-5p mimic group. Cell apoptosis was detected by flow cytometry. Cell proliferation was determined by EdU staining.

RESULTS

Compared with normal liver tissue, miR-424-5p expression was significantly decreased, while YAP1 mRNA and protein levels were obviously upregulated in liver cancer tissues, which were related to the clinical stage. A negative correlation was found between miR-424-5p and YAP1 mRNA levels in liver cancer tissues. Dual-luciferase reporter gene assay confirmed the targeted relationship between miR-424-5p and YAP1. miR-424-5p expression in HCCLM3 and MHCC97-L cells decreased compared with L20 cells, which correlated with malignancy. YAP1 level in HCCLM3 and MHCC97-L cells was significantly enhanced, which correlated with malignancy. miR-424-5p mimic transfection significantly downregulated YAP1 expression in HCCLM3 and MHCC97-L cells, resulting in enhanced apoptosis and attenuated cell proliferation.

CONCLUSIONS

Decreased miR-424-5p expression and increased YAP1 expression are found in patients with liver cancer. Increased miR-424-5p can inhibit YAP1 expression, attenuate hepatoma cell proliferation, and induce cell apoptosis.

Six-long non-coding RNA signature predicts recurrence-free survival in hepatocellular carcinoma

BACKGROUND

Recent evidence shows that long non-coding RNAs (lncRNAs) are closely related to hepatogenesis and a few aggressive features of hepatocellular carcinoma (HCC). Increasing studies demonstrate that lncRNAs are potential prognostic factors for HCC. Moreover, several studies reported the combination of lncRNAs for predicting the overall survival (OS) of HCC, but the results varied. Thus, more effort including more accurate statistical approaches is needed for exploring the prognostic value of lncRNAs in HCC.

AIM

To develop a robust lncRNA signature associated with HCC recurrence to improve prognosis prediction of HCC.

METHODS

Univariate COX regression analysis was performed to screen the lncRNAs significantly associated with recurrence-free survival (RFS) of HCC in GSE76427 for the least absolute shrinkage and selection operator (LASSO) modelling. The established lncRNA signature was validated and developed in The Cancer Genome Atlas (TCGA) series using Kaplan-Meier curves. The expression values of the identified lncRNAs were compared between the tumor and non-tumor tissues. Pathway enrichment of these lncRNAs was conducted based on the significantly co-expressed genes. A prognostic nomogram combining the lncRNA signature and clinical characteristics was constructed.

RESULTS

The lncRNA signature consisted of six lncRNAs: MSC-AS1, POLR2J4, EIF3J-AS1, SERHL, RMST, and PVT1. This risk model was significantly associated with the RFS of HCC in the TCGA cohort with a hazard ratio (HR) being 1.807 (95%CI [confidence interval]: 1.329-2.457) and log-rank P-value being less than 0.001. The best candidates of the six-lncRNA signature were younger male patients with HBV infection in relatively early tumor-stage and better physical condition but with higher preoperative alpha-fetoprotein. All the lncRNAs were significantly upregulated in tumor samples compared to non-tumor samples (P < 0.05). The most significantly enriched pathways of the lncRNAs were TGF-β signaling pathway, cellular apoptosis-associated pathways, etc. The nomogram showed great utility of the lncRNA signature in HCC recurrence risk stratification.

CONCLUSION

We have constructed a six-lncRNA signature for prognosis prediction of HCC. This risk model provides new clinical evidence for the accurate diagnosis and targeted treatment of HCC.

Bioinformatical identification of key pathways and genes in human hepatocellular carcinoma after CSN5 depletion

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer. It has been previously reported that CSN5 depletion is an effective method in human HCC. In the current study, we aimed to uncover gene signatures and key pathways during HCC. Gene expression profiles of GSE26485 were downloaded from GEO database. Totally, 101 differentially expressed genes (DEGs) were up-regulated and 146 ones were down-regulated. Biological processes (BP) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) analysis showed that the DEGs were mainly enriched in regulation of cell growth, oxidation-reduction process, mitotic cytokinesis, negative regulation of macroautophagy, endosome organization, lysosome, biosynthesis of antibiotics, small cell lung cancer and glutathione metabolism and so on (P < 0.05). Protein-protein interaction (PPI) network, Kaplan-Meier, log-rank method, western blot, immunohistochemistry and encyclopedia of DNA elements (ENCODE) analysis showed that CSN5 depletion took effects through down-regulation of SMAD5-related pathways which include EXO1, CENPA and NCAPG, resulting in the inactivation of H3K4me3 and H3K36me3. Those genes represent the promising targets for therapeutic intervention in HCC patients.