High miR-139-3p expression predicts a better prognosis for hepatocellular carcinoma: a pooled analysis

Role of immune related genes in predicting prognosis and immune response in patients with hepatocellular carcinoma

Immunotherapy has developed rapidly in recent years. This study aimed to establish a prognostic signature for immune-related genes (IRGs) and explore related potential immunotherapies. The RNA-seq transcriptome profiles and clinicopathological information of patients were obtained from The Cancer Genome Atlas. Differentially expressed IRGs in tumors and normal tissues were screened and a risk score signature was constructed to predict the prognosis in patients with hepatocellular carcinoma (HCC). Receiver operating characteristic curves, survival analyses, and correlation analyses were used to explore the clinical application of this model. We further analyzed the differences in clinical characteristics, immune infiltration, somatic mutations, and treatment sensitivity between the high- and low-risk populations characterized by the prognostic models. The immune cell infiltration score and immune-related pathway activity were calculated using the single sample gene set enrichment analysis (ssGSEA) set enrichment analysis. Gene ontology (GO), Kyoto encyclopedia of genes and genomes, and GSEA were used to explore the underlying mechanisms. We constructed a nine-IRG formula to predict the prognosis in HCC patients. The higher the risk score, the higher the malignancy of the tumor and the worse the prognosis. There were significant differences in immune related processes between the high- and low-risk groups. TP53 and CTNNB1 mutations were significantly different between different risk groups. The expression of model gene was closely related to the sensitivity of tumor cells to chemotherapeutic drugs. This risk score model, which is helpful for the individualized treatment of patients with different risk factors, could be a reliable prognostic tool for HCC patients.

Construction of a prognostic assessment model for colon cancer patients based on immune-related genes and exploration of related immune characteristics

Objectives: To establish a novel risk score model that could predict the survival and immune response of patients with colon cancer. Methods: We used The Cancer Genome Atlas (TCGA) database to get mRNA expression profile data, corresponding clinical information and somatic mutation data of patients with colon cancer. Limma R software package and univariate Cox regression were performed to screen out immune-related prognostic genes. GO (Gene ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) were used for gene function enrichment analysis. The risk scoring model was established by Lasso regression and multivariate Cox regression. CIBERSORT was conducted to estimate 22 types of tumor-infiltrating immune cells and immune cell functions in tumors. Correlation analysis was used to demonstrate the relationship between the risk score and immune escape potential. Results: 679 immune-related genes were selected from 7846 differentially expressed genes (DEGs). GO and KEGG analysis found that immune-related DEGs were mainly enriched in immune response, complement activation, cytokine-cytokine receptor interaction and so on. Finally, we established a 3 immune-related genes risk scoring model, which was the accurate independent predictor of overall survival (OS) in colon cancer. Correlation analysis indicated that there were significant differences in T cell exclusion potential in low-risk and high-risk groups. Conclusion: The immune-related gene risk scoring model could contribute to predicting the clinical outcome of patients with colon cancer.

Maternal Exercise Programs Glucose and Lipid Metabolism and Modulates Hepatic miRNAs in Adult Male Offspring

Detrimental exposures in mothers are recognized as risk factors for the development of metabolic dysfunction in offspring. In contrast, maternal exercise has been reported to be an effective strategy to maintain offspring health. However, the mechanisms underlying the protective effects of maternal exercise on adult offspring metabolic homeostasis are largely unclear. This study aims to investigate whether maternal exercise before and during pregnancy could combat the adverse effects of maternal high-fat diet (HFD) on metabolism in 24-week-old male offspring and to explore the role of miRNAs in mediating the effects. Female C57BL/6 mice were fed with either control diet or HFD 3-week prior to breeding and throughout pregnancy and lactation, among whom half of the HFD-fed mice were submitted to voluntary wheel running training 3-week before and during pregnancy. Male offspring were sedentary and fed with a control diet from weaning to 24 weeks. Body weight, the content of inguinal subcutaneous adipose tissue and perirenal visceral adipose tissue, glucose tolerance, and serum insulin and lipids in offspring were analyzed. Hepatic tissues were collected for transcriptome and miRNA sequencing and reverse transcription-quantitative polymerase chain reaction validation. The results showed that maternal HFD resulted in significant glucose intolerance, insulin resistance, and dyslipidemia in adult offspring, which were negated by maternal exercise. Transcriptome sequencing showed that maternal exercise reversed perinatal HFD-regulated genes in adult offspring, which were enriched in glucose and lipid metabolic-related signaling pathways. At the same time, maternal exercise significantly rescued the changes in the expression levels of 3 hepatic miRNAs in adult offspring, and their target genes were involved in the regulation of cholesterol biosynthesis and epigenetic modification, which may play an important role in mediating the intergenerational metabolic regulation of exercise. Overall, our research pioneered the role of miRNAs in mediating the programming effects of maternal exercise on adult offspring metabolism, which might provide novel insight into the prevention and treatment of metabolic disorders in early life.

UCK2 regulated by miR-139-3p regulates the progression of hepatocellular carcinoma cells

Objective: This study mainly explores how UCK2 impacts the progression of hepatocellular carcinoma (HCC). Methods: Mature miRNA and mRNA expression data along with the clinical data of HCC were provided by The Cancer Genome Atlas to mine differentially expressed miRNAs and mRNAs. Expression levels of UCK2 and miR-139-3p in HCC were tested through quantitative real-time PCR. How UCK2 and miR-139-3p impacted HCC cell activities were detected by Transwell, wound healing and cell proliferation approaches. Whether miR-139-3p could bind to UCK2 was detected by dual-luciferase assay. Results: This investigation found evidently high levels of UCK2 in both HCC tissue and cells and its marked association with poor prognosis. Overexpression of UCK2 could significantly promote the behaviors of HCC cells. In addition, poorly expressed miR-139-3p was inversely associated with UCK2. Dual-luciferase method also proved the association. The rescue experiment showed that miR-139-3p regulated cell behaviors in HCC through targeting UCK2. Conclusion: Highly expressed UCK2 was mediated by miR-139-3p to modulate cell behaviors in HCC. It is assumed that UCK2 is a possible target of HCC for cancer therapy purposes.

The Value of Serum miR-139-3p Expression Level in Predicting Postoperative Survival of Colon Cancer Patients

Background

To explore the value of serum miR-139-3p expression level in predicting postoperative survival of colon cancer patients.

Methods

We selected 158 cases enrolled in our hospital from January 2017 to December 2019. Using real-time fluorescence quantitative PCR, the expression extents of serum miR-139-3p among patients suffering from colon cancer were detected. The enrollment of patients was performed in the high or low miR-139-3p group on the basis of the cutoff value determined by ROC curve analysis. The risk elements influencing the postoperative survival of colon cancer patients were analyzed by the Kaplan–Meier approach and univariate and multivariate Cox regression models.

Results

Compared with control group, significantly lower expression level of serum miR-139-3p was shown in colon cancer group (P < 0.05). Its low expression of miR-139-3p was associated with TNM stage, degree of differentiation, tumor sizes, lymph node metastasis and vascular infiltration in patients with colon cancer (all P < 0.05), which was also significantly associated with short survival time of colon cancer patients (P < 0.05). Multivariate Cox regression model analysis displayed that TNM phase, lymph node metastasis and miR-139-3p <2.17 were independent risk elements affecting postoperative survival (P < 0.05).

Conclusion

The low expression level of miR-139-3p is related to the short survival time of colon cancer patients, and it is expected to be used as a biological indicator to predict the postoperative survival of colon cancer.

Circ_0003221 Downregulation Restrains Cervical Cancer Cell Growth, Metastasis and Angiogenesis by Governing the miR-139-3p/S100A14 Pathway

Circular RNA (circRNA) has considerable potency in carcinogenesis, which has aroused much attention. The objective of our study was to disclose the role of circ_0003221 in cervical cancer. Circ_0003221, miR-139-3p, and S100 calcium-binding protein A14 (S100A14) mRNA were quantified by quantitative real-time PCR (qPCR). The proliferation of cancer cells was checked by CCK-8 assay and EdU assay. The migration and invasion of cancer cells were checked by transwell assay. Angiogenesis was determined by tube formation assay. The protein levels of epithelial-mesenchymal transition (EMT)-related markers, angiogenesis-related markers, and S100A14 protein were measured by western blot. The interplays between miR-139-3p and circ_0003221 or S100A14 were ensured by RIP assay and dual-luciferase reporter assay. Further animal study was conducted to verify the role of circ_0003221 in vivo. Circ_0003221 was highly expressed in cancer tissues and cells, and its downregulation suppressed cancer cell proliferation, migration, invasion, and angiogenesis and also delayed tumor growth in vivo. Circ_0003221 bound to miR-139-3p and sequestered miR-139-3p expression. The inhibitory cancer cell biological behaviors by circ_0003221 downregulation were recovered by miR-139-3p suppression. S100A14 was a target gene of miR-139-3p. MiR-139-3p upregulation repressed cancer cell malignant phenotypes by depleting S100A14. Importantly, circ_0003221 positively regulated S100A14 expression by targeting miR-139-3p. Circ_0003221 downregulation restrains cervical cancer cell growth, metastasis, and angiogenesis by governing the miR-139-3p/S100A14 pathway.

Integrated Analysis of the m6A-Related lncRNA Identified lncRNA ABALON/miR-139-3p/NOB1 Axis Was Involved in the Occurrence of Lung Cancer

Background

Lung cancer has the characteristics of early metastasis, high recurrence, and high mortality rate despite emerging advances in diagnostic. Early diagnosis can significantly improve the patient’s chances of cure and survival.

Purpose

This study aimed to identify and assess a prognostic lncRNA/miRNA/gene signature in patients with lung cancer.

Methods

Pearson correlation analysis, univariate Cox analysis and LASSO Cox analysis were used to construct a lung cancer prognostic risk model based on m6A-related lncRNA. The interaction between lncRNA-miRNA-gene was verified by luciferase reporter gene experiment.

Results

The Pearson correlation analysis determined that 1655 lncRNAs significantly correlated with the expression of m6A genes. A lung cancer prognostic risk model, including 14 m6A-related lncRNAs, was constructed through univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) Cox analysis. ABALON was identified as the key lncRNA through cluster analysis and gene expression difference analysis.

Conclusion

It was experimentally verified that ABALON acted as a competing endogenous RNA by sponging miR-139-3p and indirectly regulated the expression of NOB1. This study provided a new biological target for the early diagnosis of lung cancer and a new direction for studying the mechanism of lung cancer.

Non-coding RNAs as biomarkers for hepatocellular carcinoma-A systematic review

Hepatocellular carcinoma (HCC) is the sixth most common malignancy in the world and the fourth leading cause of cancer-related death, and its incidence is increasing globally. Despite significant advances in treatment strategies for HCC, the prognosis is still poor due to its high recurrence rate. Therefore, there is an urgent need to understand the pathogenesis of HCC and further develop new therapies to improve the prognosis and quality of life of HCC patients. MicroRNAs (miRNAs, miRs) are small non-coding RNAs involved in post-transcriptional regulation of gene expression that is abnormally expressed in cancer-associated genomic regions or vulnerable sites. More and more findings have shown that miRNAs are important regulatory factors of mRNA expression in HCC, and they are receiving more and more attention as a possible key biomarker of HCC. This review mainly summarizes the potential applied value on miRNAs as diagnostic, drug resistant, prognostic, and therapeutic biomarkers in the diagnosis, therapy, and prognosis of HCC. Also, we summarize the research value of long non-coding RNA (lncRNAs), circular RNAs (circRNAs), and miRNAs network in HCC as novel biomarkers, aiming at providing some references for the therapy of HCC.

Proliferating cell nuclear antigen clamp associated factor, a potential proto-oncogene with increased expression in malignant gastrointestinal tumors

Gastrointestinal (GI) cancers, including malignancies in the gastrointestinal tract and accessory organs of digestion, represent the leading cause of death worldwide due to the poor prognosis of most GI cancers. An investigation into the potential molecular targets of prediction, diagnosis, prognosis, and therapy in GI cancers is urgently required. Proliferating cell nuclear antigen (PCNA) clamp associated factor (PCLAF), which plays an essential role in cell proliferation, apoptosis, and cell cycle regulation by binding to PCNA, is a potential molecular target of GI cancers as it contributes to a series of malignant properties, including tumorigenesis, epithelial-mesenchymal transition, migration, and invasion. Furthermore, PCLAF is an underlying plasma prediction target in colorectal cancer and liver cancer. In addition to GI cancers, PCLAF is also involved in other types of cancers and autoimmune diseases. Several pivotal pathways, including the Rb/E2F pathway, NF-κB pathway, and p53-p21 cascade, are implicated in PCLAF-mediated diseases. PCLAF also contributes to some diseases through dysregulation of the p53 pathway, WNT signal pathway, MEK/ERK pathway, and PI3K/AKT/mTOR signal cascade. This review mainly describes in detail the role of PCLAF in physiological status and GI cancers. The signaling pathways involved in PCLAF are also summarized. Suppression of the interaction of PCLAF/PCNA or the expression of PCLAF might be potential biological therapeutic strategies for GI cancers.

CENPL, ISG20L2, LSM4, MRPL3 are four novel hub genes and may serve as diagnostic and prognostic markers in breast cancer

As a highly prevalent disease among women worldwide, breast cancer remains in urgent need of further elucidation its molecular mechanisms to improve the patient outcomes. Identifying hub genes involved in the pathogenesis and progression of breast cancer can potentially help to unveil mechanism and also provide novel diagnostic and prognostic markers. In this study, we integrated multiple bioinformatic methods and RNA in situ detection technology to identify and validate hub genes. EZH2 was recognized as a key gene by PPI network analysis. CENPL, ISG20L2, LSM4, MRPL3 were identified as four novel hub genes through the WGCNA analysis and literate search. Among these, many studies on EZH2 in breast cancer have been reported, but no studies are related to the roles of CENPL, ISG20L2, MRPL3 and LSM4 in breast cancer. These four novel hub genes were up-regulated in tumor tissues and associated with cancer progression. The receiver operating characteristic analysis and Kaplan-Meier survival analysis indicated that these four hub genes are promising candidate genes that can serve as diagnostic and prognostic biomarkers for breast cancer. Moreover, these four newly identified hub genes as aberrant molecules in the maintenance of breast cancer development, their exact functional mechanisms deserve further in-depth study.

LncRNA H19 Aggravates Intervertebral Disc Degeneration by Promoting the Autophagy and Apoptosis of Nucleus Pulposus Cells Through the miR-139/CXCR4/NF-κB Axis

The etiology of lumbocrural pain is closely related to intervertebral disc degeneration (IDD). Long noncoding RNAs (lncRNAs) serve crucial roles in IDD progression. This study investigated the effect of lncRNA H19 on autophagy and apoptosis of nucleus pulposus cells (NPCs) in IDD. The rat model of IDD was established. Normal NPCs and degenerative NPCs (DNPCs) were cultured in vitro. H19 expression in IDD rat was detected. DNPCs were treated with si-H19 to evaluate autophagy and apoptosis of DNPCs. The binding relationships between H19 and miR-139-3p, and miR-139-3p and CXCR4 were verified. DNPCs were co-transfected si-H19 and miR-139-3p inhibitor. The phosphorylation of NF-κB pathway-related p65 in DNPCs was detected. LncRNA H19 was upregulated in IDD rats. Downregulation of H19 inhibited autophagy and apoptosis of DNPCs. LncRNA H19 sponged miR-139-3p to inhibit CXCR4 expression. si-H19 and miR-139-3p inhibitor co-treatment induced autophagy and apoptosis, and enhanced CXCR4 expression. si-H19 decreased p-p65 phosphorylation, while si-H19 and miR-139-3p inhibitor co-treatment partially elevated p-p65 phosphorylation. In conclusion, lncRNA H19 facilitated the autophagy and apoptosis of DNPCs by the miR-139-3p/CXCR4/NF-κB axis, thereby aggravating IDD. This study may offer new insights for the management of IDD.

Identification of Key Genes With Differential Correlations in Lung Adenocarcinoma

BACKGROUND

With the advent of large-scale molecular profiling, an increasing number of oncogenic drivers contributing to precise medicine and reshaping classification of lung adenocarcinoma (LUAD) have been identified. However, only a minority of patients archived improved outcome under current standard therapies because of the dynamic mutational spectrum, which required expanding susceptible gene libraries. Accumulating evidence has witnessed that understanding gene regulatory networks as well as their changing processes was helpful in identifying core genes which acted as master regulators during carcinogenesis. The present study aimed at identifying key genes with differential correlations between normal and tumor status.

METHODS

Weighted gene co-expression network analysis (WGCNA) was employed to build a gene interaction network using the expression profile of LUAD from The Cancer Genome Atlas (TCGA). R package DiffCorr was implemented for the identification of differential correlations between tumor and adjacent normal tissues. STRING and Cytoscape were used for the construction and visualization of biological networks.

RESULTS

A total of 176 modules were detected in the network, among which yellow and medium orchid modules showed the most significant associations with LUAD. Then genes in these two modules were further chosen to evaluate their differential correlations. Finally, dozens of novel genes with opposite correlations including ATP13A4-AS1, HIGD1B, DAP3, and ISG20L2 were identified. Further biological and survival analyses highlighted their potential values in the diagnosis and treatment of LUAD. Moreover, real-time qPCR confirmed the expression patterns of ATP13A4-AS1, HIGD1B, DAP3, and ISG20L2 in LUAD tissues and cell lines.

CONCLUSION

Our study provided new insights into the gene regulatory mechanisms during transition from normal to tumor, pioneering a network-based algorithm in the application of tumor etiology.

Identification of a five-immune gene model as an independent prognostic factor in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a common malignant tumor with a poor prognosis. We aimed to identify a new prognostic model of HCC based on differentially expressed (DE) immune genes.

METHODS

The DE immune genes were identified based on an analysis of 374 cases of HCC and 50 adjacent non-tumor specimens from the Cancer Genome Atlas (TCGA) database. Univariate Cox analysis, Lasso regression, and multivariate Cox analysis were used to construct the model based on the training group. Survival analysis and the receiver operating characteristic (ROC) curves were used to evaluate model performance. The testing group and the entire group were subsequently used for validation of the model.

RESULTS

A five-immune gene model consisted of HSPA4, ISG20L2, NDRG1, EGF, and IL17D was identified. Based on the model, the overall survival was significantly different between the high-risk and low-risk groups (P = 7.953e-06). The AUCs for the model at 1- and 3-year were 0.849 and 0.74, respectively. The reliability of the model was confirmed using the validation groups. The risk score was identified as an independent prognostic parameter and closely related to the content of immune cells from human HCC specimens.

CONCLUSION

We identified a five-immune gene model that can be used as an independent prognostic marker for HCC.

Identification of a DNA Repair Gene Signature and Establishment of a Prognostic Nomogram Predicting Biochemical-Recurrence-Free Survival of Prostate Cancer

Background: The incidence of prostate cancer (PCa) is high and increasing worldwide. The prognosis of PCa is relatively good, but it is important to identify the patients with a high risk of biochemical recurrence (BCR) so that additional treatment could be applied.

Method: Level 3 mRNA expression and clinicopathological data were obtained from The Cancer Genome Atlas (TCGA) to serve as training data. The GSE84042 dataset was used as a validation set. Univariate Cox, lasso Cox, and stepwise multivariate Cox regression were applied to identify a DNA repair gene (DRG) signature. The performance of the DRG signature was assessed based on Kaplan–Meier curve, receiver operating characteristic (ROC), and Harrell’s concordance index (C-index). Furtherly, a prognostic nomogram was established and evaluated likewise.

Results: A novel four DRG signature was established to predict BCR of PCa, which included POLM, NUDT15, AEN, and HELQ. The ROC and C index presented good performance in both training dataset and validation dataset. The patients were stratified by the signature into high- and low-risk groups with distinct BCR survival. Multivariate Cox analysis revealed that the DRG signature is an independent prognostic factor for PCa. Also, the DRG signature high-risk was related to a higher homologous recombination deficiency (HRD) score. The nomogram, incorporating the DRG signature and clinicopathological parameters, was able to predict the BCR with high efficiency and showed superior performance compared to models that consisted of only clinicopathological parameters.

Conclusion: Our study identified a DRG signature and established a prognostic nomogram, which were reliable in predicting the BCR of PCa. This model could help with individualized treatment and medical decision making.

MicroRNA signature in liver cancer

Liver cancer is the 7^th utmost frequent neoplasm and the 4^th principal source of cancer deaths. This malignancy is linked with several environmental and lifestyle-related factors emphasizing the role of epigenetics in its pathogenesis. MicroRNAs (miRNAs) have been regarded as potent epigenetic mechanisms partaking in the pathogenesis of liver cancer. Dysregulation of miRNAs has been related with poor outcome of patients with liver cancer. In the current manuscript, we provide a concise review of the results of recent studies about the role of miRNAs in the progression of liver cancer and their diagnostic and prognostic utility.

LncRNA PCAT6 regulates the progression of pituitary adenomas by regulating the miR-139-3p/BRD4 axis

BACKGROUND

Dysregulated lncRNA PCAT6 was discovered in many cancers excluding pituitary adenomas (PA). Therefore, we explored the role of PCAT6 in PA in this research.

METHODS

Abnormally expressed miRNAs were analyzed by bioinformatics and RT-qPCR. The target and regulator of miR-139-3p were determined by bioinformatics, dual-luciferase reporter assay, or RIP. The correlation among PCAT6, miR-139-3p, and BRD4 was further analyzed. The viability, apoptosis, cell cycle distribution of PA cells, as well as their ability to invade, migrate, and proliferate, were tested after transfection through CCK-8, flow cytometry, transwell, wound healing, and colony formation assays. After construction of transplanted-tumor model in nude mice, cell apoptosis in the tumor was detected by TUNEL. The expressions of PCAT6, BRD4, miR-139-3p, and apoptosis-related factors in PA tissues, cells, or tumor tissues were detected by RT-qPCR, Western blot, or IHC.

RESULTS

PCAT6 and BRD4 were high-expressed but miR-139-3p was low-expressed in PA. Both the 3'-untranslated regions of PCAT6 and BRD4 mRNAs were demonstrated to contain a potential binding site for miR-139-3p. PCAT6 was positively correlated to BRD4, and miR-139-3p was negatively correlated to PCAT6 and BRD4. MiR-139-3p mimic, shPCAT6 and siBRD4 inhibited the viability, migration, invasion, and proliferation of PA cells while inducing apoptosis. MiR-139-3p mimic and shPCAT6 inhibited the cell cycle progression of PA cells, decreased the weight and volume of the xenotransplanted tumor, and reduced the levels of Bcl-2 and BRD4 while enhancing the levels of Bax, miR-139-3p, and Cleaved caspase-3. MiR-139-3p inhibitor caused the opposite effect of miR-139-3p mimic and further reversed the effect of shPCAT6 on on PA cells.

CONCLUSION

PCAT6 regulated the progression of PA via modulating the miR-139-3p/BRD4 axis, which might provide a novel biomarker for the prevention, diagnosis, and treatment of PA.

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.

Integrated Analysis of Immunity- and Ferroptosis-Related Biomarker Signatures to Improve the Prognosis Prediction of Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is a common malignant tumor with high mortality and poor prognoses around the world. Ferroptosis is a new form of cell death, and some studies have found that it is related to cancer immunotherapy. The aim of our research was to find immunity- and ferroptosis-related biomarkers to improve the treatment and prognosis of HCC by bioinformatics analysis.

Methods

First, we obtained the original RNA sequencing (RNA-seq) expression data and corresponding clinical data of HCC from The Cancer Genome Atlas (TGCA) database and performed differential analysis. Second, we used immunity- and ferroptosis-related differentially expressed genes (DEGs) to perform a computational difference algorithm and Cox regression analysis. Third, we explored the potential molecular mechanisms and properties of immunity- and ferroptosis-related DEGs by computational biology and performed a new prognostic index based on immunity- and ferroptosis-related DEGs by multivariable Cox analysis. Finally, we used HCC data from International Cancer Genome Consortium (ICGC) data to perform validation.

Results

We obtained 31 immunity (p < 0.001)- and 14 ferroptosis (p < 0.05)-related DEGs correlated with overall survival (OS) in the univariate Cox regression analysis. Then, we screened five immunity- and two ferroptosis-related DEGs (HSPA4, ISG20L2, NRAS, IL17D, NDRG1, ACSL4, and G6PD) to establish a predictive model by multivariate Cox regression analysis. Receiver operating characteristic (ROC) and Kaplan–Meier (K–M) analyses demonstrated a good performance of the seven-biomarker signature. Functional enrichment analysis including Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed that the seven-biomarker signature was mainly associated with HCC-related biological processes such as nuclear division and the cell cycle, and the immune status was different between the two risk groups.

Conclusion

Our results suggest that this specific seven-biomarker signature may be clinically useful in the prediction of HCC prognoses beyond conventional clinicopathological factors. Moreover, it also brings us new insights into the molecular mechanisms of HCC.

Expression and Regulatory Network Analysis of MiR-139-3p, a New Potential Serum Biomarker for Esophageal Squamous Cell Carcinoma Based on Bioinformatics Analysis

Background:

In recent studies, microRNAs have been demonstrated as stable detectable biomarkers in blood for cancer. In addition, computer-aided biomarker discovery has now become an attractive paradigm for precision diagnosis.

Methods:

In this study, we identified and evaluated miR-139-3p as a biomarker for screening of esophageal squamous cell carcinoma using the Cancer Genome Atlas and Gene Expression Omnibus database analyses. We identified possible miR-139-3p target genes through the predicted database and esophageal squamous cell carcinoma upregulated genes from the Cancer Genome Atlas and Gene. Bioinformatics analysis was performed to determine key miR-139-3p targets and pathways associated with esophageal carcinoma. Finally, the expression and expected significance of hub genes were evaluated via the Genotype-Tissue Expression project.

Results:

MiR-139-3p was significantly downregulated in patients with esophageal squamous cell carcinoma/esophageal carcinoma. In GSE 122497, the area under the curve-receiver operating characteristic value, sensitivity, and specificity for serum miR-139-3p were 0.754, 67.49%, and 80.00%, respectively. The pattern specification process, skeletal system development, and regionalization process were the most enriched interactions in esophageal carcinoma. In addition, Epstein-Barr virus infection, human T-cell leukemia virus 1 infection, and human cytomegalovirus infection were identified as crucial pathways. Six hub genes (CD1A, FCGR2A, ANPEP, CD1B, membrane metalloendopeptidase, and TWIST1) were found, and FCGR2A and membrane metalloendopeptidase were further confirmed by genotype-tissue expression. High expression of membrane metalloendopeptidase correlated with a better overall survival but not with disease-free survival of patients with esophageal carcinoma.

Conclusions:

MiR-139-3p was identified as a candidate biomarker for predicting esophageal squamous cell carcinoma based on network analysis. MiR-139-3p acted as a tumor suppressor by targeting membrane metalloendopeptidase in esophageal carcinoma, and low expression of membrane metalloendopeptidase may indicate a better prognosis of patients with esophageal carcinoma.

LncRNA MEG3 rs3087918 was associated with a decreased breast cancer risk in a Chinese population: a case-control study

Background

LncRNA MEG3 expressed abnormally in various cancers including breast cancer, but no studies reported the correlation between MEG3 SNPs and breast cancer susceptibility among Chinese women.

Methods

This study is aimed to explore the association between three SNPs of MEG3 (rs3087918, rs7158663, rs11160608) and breast cancer. The study is a population-based case-control study including 434 breast cancer patients and 700 healthy controls. Genotyping was performed using Sequenom MassArray technique. Function prediction of rs3087918 were based on RNAfold and lncRNASNP2 databases.

Results

Pooled analysis indicated that rs3087918 was related to a decreased risk of breast cancer [GG vs. TT: OR (95%) = 0.67(0.45–0.99), P = 0.042; GG vs. TT + TG: OR (95%) = 0.69(0.48–0.99), P = 0.046], especially for women aged <=49 [GG vs. TT: OR (95%) = 0.40(0.22–0.73), P = 0.02]. Comparison between case groups showed genotype GG and TG/GG of rs3087918 were associated with her-2 receptor expression [GG vs. TT: OR (95%) = 2.37(1.24–4.63), P = 0.010; TG + GG vs. TT: OR (95%) = 1.50(1.01–2.24), P = 0.045]. We didn’t find statistical significance for rs11160608, rs7158663 and breast cancer. Structure prediction based on RNAfold found rs3087918 may influence the secondary structure of MEG3. The results based on lncRNASNP2 indicated that rs3087918 may gain the targets of hsa-miR-1203 to MEG3, while loss the target of hsa-miR-139-3p and hsa-miR-5091 to MEG3.

Conclusions

MEG3 rs3087918 was associated with a decreased risk of breast cancer. MEG3 haplotype TCG may increase the risk of breast cancer.

Clinical value of LHPP-associated microRNAs combined with protein induced by vitamin K deficiency or antagonist-II in the diagnosis of alpha-fetoprotein-negative hepatocellular carcinoma

Background

Alpha‐fetoprotein (AFP) has received extensive attention in the differential diagnosis of hepatocellular carcinoma (HCC), especially for AFP‐negative HCC (AFP‐NHCC). The current study aimed to explore the value of targeted regulation of LHPP expression‐related microRNAs (miRs) and protein induced by vitamin K deficiency or antagonist‐II (PIVKA‐II) in the differential diagnosis of AFP‐NHCC.

Methods

A retrospective study was conducted on a testing set—including 214 AFP‐NHCC patients, 200 cirrhosis, and 210 controls, and a validation set—including 140 AFP‐NHCC patients, 134 cirrhosis, and 128 controls recruited from The First Affiliated Hospital of Hunan Normal University. Serum miRs were examined using quantitative real‐time PCR method. Serum PIVKA‐II was measured by enzyme‐linked immunosorbent assay.

Results

Compared with adjacent tissues, LHPP protein levels in cancer tissues were significantly decreased (P < .05). Predictive software and dual‐luciferase reporter assays showed that miR‐363‐5p and miR‐765 can target LHPP expression. Serum miR‐363‐5p, miR‐765, and PIVKA‐II levels were significantly higher in AFP‐HCC patients than in cirrhosis and controls. A logistic regression model combining miR‐363‐5p, miR‐765, and PIVKA‐II was performed. This model presented a high discriminating value (AUC: 0.930, sensitivity/specificity: 79.4%/95.4%) than any single indicator. In the validation set, this model still showed a high discriminating value (AUC: 0.936, sensitivity/specificity: 83.6%/94.7%).

Conclusion

Current model combining serum miR‐363‐5p, miR‐765, and PIVKA‐II has potential significance for diagnosis of AFP‐NHCC.