Yun He

Overexpression of LncRNA HOTAIR is Associated with Poor Prognosis in Thyroid Carcinoma: A Study Based on TCGA and GEO Data

The role of long non-coding RNA (lncRNA) HOX transcript antisense RNA (HOTAIR) in thyroid carcinoma (TC) remains unclear. The current study was aimed to assess the clinical value of HOTAIR expression levels in TC based on publically available data and to evaluate its potential signaling pathways. The expression data of HOTAIR and clinical information concerning TC were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), respectively. Furthermore, 3 online biological databases, Starbase, Cbioportal, and Multi Experiment Matrix, were used to identify HOTAIR-related genes in TC. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Panther pathway analyses were then undertaken to study the most enriched signaling pathways in TC (EASE score<0.1, Bonferroni<0.05). The TCGA results demonstrated that the expression level of HOTAIR in TC tissues was significantly increased compared with non-cancerous tissues (p<0.001). HOTAIR over-expression was significantly associated with poor survival in TC patients (p=0.03). Meta-analyses of GEO datasets revealed a trend consistent with the above results on HOTAIR expression levels in TC (SMD=0.23; 95%CI, 0.00-0.45; p=0.047). Finally, the results of functional analysis for HOTAIR-related genes indicated that HOTAIR might participate in tumorigenesis via the Wnt signaling pathway. In conclusion, our study demonstrates that HOTAIR may be involved in thyroid carcinogenesis, and the over-expression of HOTAIR could act as a biomarker associated with a poor outcome in TC patients. Moreover, the Wnt signaling pathway may be the key pathway regulated by HOTAIR in TC.

Diagnostic and prognostic roles of IRAK1 in hepatocellular carcinoma tissues: an analysis of immunohistochemistry and RNA-sequencing data from the cancer genome atlas

Background IRAK1 has been repoted to play an essential role in the development of multiple cancers. However, the clinical significance of IRAK1 in hepatocellular carcinoma (HCC) and the underlying molecular mechanism remain unclear. Therefore, we aimed to investigate the role of IRAK1 in the pathogenesis of HCC in this study. Materials and methods HCC tissues and para-carcinoma tissues were collected for immunohistochemistry (IHC) analysis to evaluate IRAK1 expression. Data of IRAK1 expression were downloaded from the cancer genome atlas (TCGA) for analyzing the clinical significance of IRAK1. Receiver operating characteristic (ROC) curve and survival analyses were carried out to assess the diagnostic and prognostic significance of IRAK1 in IHC and TCGA data. Additionally, we investigated the alteration of IRAK1 gene in HCC from cBioPortal to generate a network of the interaction between IRAK1 and the neighboring genes. The influence of IRAK1 gene alteration on the prognosis of HCC patients was evaluated by survival analysis. Results Analysis of both IHC and TCGA data revealed a significant upregulation of IRAK1 in HCC tissues. The IHC analysis revealed there was an increasing trend in IRAK1 expression among normal liver tissues, liver cirrhosis tissues, para-carcinoma tissues and HCC tissues. The ROC curves for IHC and TCGA data demonstrated that IRAK1 exhibited a significant diagnostic value for HCC. Moreover, IRAK1 expression was observed to be associated with tumor size, metastasis and T-stage. The survival analysis indicated that the upregulation of IRAK1 predicted a worse overall survival of HCC. Additionally, data from cBioPortal confirmed that 29% of HCC tissues possessed an alteration of the IRAK1 gene. Conclusion IRAK1 may act as an oncogene in the development of HCC with its overexpression in HCC. Moreover, IRAK1 might serve as a promising diagnostic and therapeutic target for HCC.

Quantitative Analysis of Hepatic Microcirculation in Rabbits After Liver Ischemia-Reperfusion Injury Using Contrast-Enhanced Ultrasound

Previous studies have shown that contrast-enhanced ultrasound (CEUS) can be used quantitatively to analyze microcirculation blood perfusion in hepatocellular carcinoma patients. However, limited data have described the application of CEUS in hepatic microcirculation after liver ischemic-reperfusion injury (IRI). The purpose of this study was to explore the use of CEUS quantitatively to assess liver microcirculation after liver IRI. We randomly sorted 45 New Zealand rabbits into 3 groups (15 in each). Group A was a control group in which the rabbits underwent laparotomy alone. In groups B and C, hepatic blood was blocked for 30xa0min. Simultaneously, rabbits in group C underwent left lateral lobe resection. After 30xa0min of ischemia, CEUS was conducted after 0xa0h, 1xa0h, 6xa0h and 24xa0h of reperfusion in the 3 groups. Time-intensity curves (TICs) for CEUS were constructed and quantitative parameters (maximum intensity [IMAX], rise time [RT], time to peak [TTP] and mean transit time [mTT]) were obtained. In addition, serum aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels were computed to estimate liver function before the operation and at 0xa0h, 1xa0h, 6xa0h and 24xa0h after reperfusion, respectively. Pathologic changes in the liver after reperfusion were also observed. Simultaneously, the correlations between serum transaminase and a variety of quantitative analysis parameters were analyzed. In groups B and C, the IMAX value decreased; whereas RT, TTP, mTT and serum ALT and AST levels increased significantly in comparison with those in group A after 0xa0h and 1xa0h of reperfusion. The pathology revealed that erythrocytes were destroyed and microcirculation was disturbed. Then, at 6xa0h of reperfusion, the IMAX continued to decrease. Additionally, the levels of RT, TTP, mTT and serum ALT and AST increased in comparison with those at 1xa0h of reperfusion. The pathologic analysis revealed inflammatory cell aggregation and leukocyte infiltration. After 24xa0h of reperfusion, the IMAX was reduced in comparison with that of the 6-h group. The levels of RT, TTP, mTT and serum ALT and serum AST were increased in comparison with that of the 6-h group. These findings were in accordance with the pathologic analysis. In addition, serum transaminase had a negative correlation with IMAX (p < 0.001) and a positive correlation with RT, TTP and mTT (all p < 0.001). So, in conclusion, the quantitative analysis of CEUS can be used to assess hepatic microcirculation after liver IRI.

RNA-sequencing investigation identifies an effective risk score generated by three novel lncRNAs for the survival of papillary thyroid cancer patients

Scholars are striving to apply molecular biology involving long non-coding RNA (lncRNA) in the prognostication of papillary thyroid cancer (PTC). However, the clinical role of lncRNAs in the prognostic setting of PTC is still unclear. Herein, a comprehensive inquiry was performed to screen lncRNA expression profiling with 507 PTC patients from The Cancer Genome Atlas RNA-sequencing datasets. A total of 734 lncRNAs were detected to be aberrantly expressed, among which three novel lncRNAs including AC079630.2, CRNDE and CTD-2171N6.1 were markedly related to the progression and survival of PTC. Furthermore, the aberrant expression of these lncRNAs could be verified by other cohorts from gene expression omnibus (GEO) as detected by microarrays. Next, we established a three-lncRNA signature and divided the PTC patients into two subgroups of high- and low-risk. Interestingly, patients with high-risk tended to gain obviously poorer outcome. Most importantly, this three-lncRNA signature was an independent biomarker to predict the patient survival of PTC. The accurate molecular roles of these three lncRNAs remains unclarified and warrants further characterization, but our current data propose that they might play pivotal roles in PTC tumorigenesis and more importantly, these novel lncRNAs are closely related to patients’ survival. These discoveries will have far-reaching consequences with respect to molecular prediction of PTC.Scholars are striving to apply molecular biology involving long non-coding RNA (lncRNA) in the prognostication of papillary thyroid cancer (PTC). However, the clinical role of lncRNAs in the prognostic setting of PTC is still unclear. Herein, a comprehensive inquiry was performed to screen lncRNA expression profiling with 507 PTC patients from The Cancer Genome Atlas RNA-sequencing datasets. A total of 734 lncRNAs were detected to be aberrantly expressed, among which three novel lncRNAs including AC079630.2, CRNDE and CTD-2171N6.1 were markedly related to the progression and survival of PTC. Furthermore, the aberrant expression of these lncRNAs could be verified by other cohorts from gene expression omnibus (GEO) as detected by microarrays. Next, we established a three-lncRNA signature and divided the PTC patients into two subgroups of high- and low-risk. Interestingly, patients with high-risk tended to gain obviously poorer outcome. Most importantly, this three-lncRNA signature was an independent biomarker to predict the patient survival of PTC. The accurate molecular roles of these three lncRNAs remains unclarified and warrants further characterization, but our current data propose that they might play pivotal roles in PTC tumorigenesis and more importantly, these novel lncRNAs are closely related to patients survival. These discoveries will have far-reaching consequences with respect to molecular prediction of PTC.

The diagnostic and prognostic values of Ki-67/MIB-1 expression in thyroid cancer: a meta-analysis with 6,051 cases

Background Growing evidence has demonstrated that Ki-67/MIB-1 has an effect on the clinical progression and prognosis in cancers. However, the diagnostic and prognostic values of Ki-67/MIB-1 in thyroid cancer remain unclear. Materials and methods The meta-analysis was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Studies were retrieved from PubMed, EBSCO, EMBASE, ISI Web of Science, China National Knowledge Infrastructure, WanFang and Chinese VIP databases. MetaDiSc and STATA12.0 were used to analyze the meta-analysis. Fixed-effect analysis and random-effect analysis were applied to pool the relative ratio based on heterogeneity in this meta-analysis. Results In the meta-analysis, 51 eligible studies were included. The pooled sensitivity of Ki-67/MIB-1 was 0.61 (95% confidence interval [CI]: 0.59–0.63) and specificity was 0.75 (95% CI: 0.74–0.77) in thyroid cancer. The pooled positive likelihood ratio was 3.19 (95% CI: 2.30–4.42) and negative likelihood ratio was 0.43 (95% CI: 0.35–0.54). In the diagnosis of thyroid cancer, the pooled diagnostic odds ratio of Ki-67/MIB-1 was 8.54 (95% CI: 5.03–14.49). The area under the symmetric receiver operating characteristic curve was 0.804 (standard error =0.031). Our results showed that there were statistical associations between Ki-67/MIB-1 and age (odds ratio [OR] =1.71, 95% CI: 1.14–2.57, P=0.010), tumor size (OR =1.86, 95% CI: 1.17–2.96, P=0.008), lymph node metastasis (OR =2.49, 95% CI: 1.42–4.39, P=0.002), metastasis status (OR =6.96, 95% CI: 2.46–19.69, P<0.001), tumor node metastasis stage (OR =6.56, 95% CI: 3.80–11.34, P<0.001) and extrathyroid extension (OR =1.91, 95% CI: 1.27–2.87, P=0.002). Furthermore, thyroid cancer patients with a high level of Ki-67/MIB-1 had a worse disease-free survival as compared to patients with a low level of Ki-67/MIB-1 (hazard ratio =5.19, 95% CI: 3.18–8.46, P<0.001). Also, Ki-67/MIB-1 was found to be associated with increased risk of mortality (hazard ratio =3.56, 95% CI: 1.17–10.83, P=0.025). Conclusion Our results demonstrated that Ki-67/MIB-1 might act as a potential factor in diagnosing thyroid cancer in Chinese. Also, the meta-analysis indicated that Ki-67/MIB-1 might have an effect on prognosis in non-Chinese thyroid cancer patients.

The anticipating value of PLK1 for diagnosis, progress and prognosis and its prospective mechanism in gastric cancer: a comprehensive investigation based on high-throughput data and immunohistochemical validation

Polo-like kinase 1 (PLK1) is a multi-functional protein and its aberrant expression is a driver of cancerous transformation and progression. To increase our understanding of the clinical value and potential molecular mechanism of PLK1 in gastric cancer (GC), we performed this comprehensive investigation. A total of 25 datasets and 12 publications were finally incorporated. Additional immunohistochemistry was conducted to validate the expression pattern of PLK1 in GC. The pooled standard mean deviation (SMD) indicated that PLK1 mRNA was up-regulated in GC (SMD=1.21, 95% CI: 0.65-1.77, P< 0.001). Similarly, the pooled odds ratio (OR) revealed that PLK1 protein was overexpressed in GC compared with normal gastric tissue (OR=12.12, 95% CI: 5.41-27.16, P<0.001). The area under the curve (AUC) of the summary receiver operating characteristic (SROC) curve was 0.86. Furthermore, our results demonstrated that GC patients with PLK1 overexpression were significantly associated with unfavorable overall survival (HR =1.54, 95% CI: 1.30–1.83, P<0.001), lymph node metastasis (OR = 1.78, 95% CI: 1.13–2.80, P=0.013) and advanced TNM stage (OR=1.48, 95% CI: 1.02-2.15, P=0.038). Altogether, 100 similar genes were identified by Gene Expression Profiling Interactive Analysis (GEPIA) and further with gene-set enrichment analysis. These genes were related to gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways relevant to the cell cycle. Gene set enrichment analysis (GSEA) indicated that PLK1 is associated with various cancer-related pathways. Collectively, this study suggests that PLK1 overexpression could play vital roles in the carcinogenesis and deterioration of GC via regulating tumor-related pathways.

Biological function of UCA1 in hepatocellular carcinoma and its clinical significance: Investigation with in vitro and meta-analysis

Urothelial cancer associated 1 (UCA1) was upregulated in hepatocellular carcinoma (HCC) tissues and cell lines, and the expression of UCA1 was associated with several clinical features and malignant behaviours in HCC. However, none of these findings completely interpreted the role of UCA1 in HCC. We conducted this investigation to validate the expression of UCA1 and its relationship with Tumor Node Metastasis (TNM) stage in 41 HCC tissues and their paired noncancerous adjacent tissues by real-time qPCR. Furthermore, we also explored the biological functions of UCA1 in vitro with HCC cell lines. Most importantly, we conducted a comprehensive meta-analysis and bioinformatics investigation based on peer-reviewed literature and in silico approaches to further summarise the clinical value and functions of UCA1 in HCC. UCA1 expression was remarkably upregulated in HCC tissues, and its expression was profoundly higher in advanced stages than in early stages. Reducing the expression levels of UCA1 suppressed the proliferation and induced apoptosis of HCC cells. Furthermore, the present meta-analysis validated that up-regulated UCA1 was closely related to larger tumour size and advanced TNM stages, and the overexpression of UCA1 was significantly correlated with a shorter OS. Additionally, according to GO analysis, the target genes were found concentrated in the following biological processes: extracellular matrix organisation, cilium assembly and cilium morphogenesis. KEGG pathway analysis showed that the UCA1-related genes were significantly enriched in the following pathways: hippo signalling pathway, bile secretion and gastric acid secretion. This evidence hinted that UCA1 could play an indispensable proliferation-related key role in HCC via the hippo signalling pathway. However, the exact molecular mechanism needs to be verified with future functional experiments.

An autophagy-related gene expression signature for survival prediction in multiple cohorts of hepatocellular carcinoma patients

Prognostic signatures have been proposed as clinical tools to estimate prognosis in hepatocellular carcinoma (HCC), which is the second most common contributor to cancer-related death at present globally. Autophagy-related genes play a dynamic and fundamental role in HCC, but knowledge of their utility as prognostic markers is limited. Here, we facilitated univariate and multivariate Cox proportional hazards regression analyses to reveal that 3 autophagy-related genes (BIRC5, FOXO1 and SQSTM1) were closely related to the survival of HCC. Then, we generated a prognosis index (PI) for predicting overall survival (OS) based on the three genes, which was an independent prognostic indicator for the OS of HCC (HR = 1.930, 95% CI: 1.200–3.104, P = 0.007). The PI showed moderate performance for predicting the survival of HCC patients and its efficacy was validated by data from three microarrays (GSE10143, GSE10186 and GSE17856). Furthermore, we deeply mined the integrated large-scale datasets from public microarrays and immunohistochemistry to validate the overexpression of BIRC5 and SQSTM1 while down-regulated FOXO1 expression in HCC. Bioinformatic analysis offered the hypothesis that proliferative signals in high-risk HCC patients were disturbing and thereby facilitated inferior clinical outcomes. Collectively, the prognostic signature we proposed is a promising biomarker for monitoring outcome of HCC. Nevertheless, prospective experimental studies are needed to validate the clinical utility.

Survival analysis of genome-wide profiles coupled with Connectivity Map database mining to identify potential therapeutic targets for cholangiocarcinoma

Cholangiocarcinoma (CCA) is one of the most common epithelial cell malignancies worldwide. However, its prognosis is poor. The aim of the present study was to examine the prognostic landscape and potential therapeutic targets for CCA. RNA sequencing data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) dataset and processed. A total of 172 genes that were significantly associated with overall survival of patients with CCA were identified using the univariate Cox regression method. Bioinformatics tools were applied using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO). It was identified that ‘Wnt signaling pathway’, ‘cytoplasm’ and ‘AT DNA binding’ were the three most significant GO categories of CCA survival-associated genes. ‘Transcriptional misregulation in cancer’ was the most significant pathway identified in the KEGG analysis. Using the Drug-Gene Interaction database, a drug-gene interaction network was constructed, and 31 identified genes were involved in it. The most meaningful potential therapeutic targets were selected via protein-protein and gene-drug interactions. Among these genes, polo-like kinase 1 (PLK1) was identified to be a potential target due to its significant upregulation in CCA. To rapidly find molecules that may affect these genes, the Connectivity Map was queried. A series of molecules were selected for their potential anti-CCA functions. 0297417-0002B and tribenoside exhibited the highest connection scores with PLK1 via molecular docking. These findings may offer novel insights into treatment and perspectives on the future innovative treatment of CCA.

Genomic analysis of small nucleolar RNAs identifies distinct molecular and prognostic signature in hepatocellular carcinoma

As one of the most lethal malignancies worldwide, hepatocellular carcinoma (HCC) has a high mortality rate, which is mainly due to the complex and multi‑step aberrations in gene expression associated with it. Small nucleolar RNAs (snoRNAs), non‑coding RNAs that are 60‑300xa0nucleotides in length, have been proposed to be closely associated with numerous human diseases, including HCC. However, the current knowledge regarding their clinical significance and mechanistic roles in HCC is limited. The present study comprehensively analyzed the snoRNA expression profiles in HCC and identified several ones that were dysregulated. The potential regulatory mechanisms of these snoRNAs were assessed via gene functional enrichment analyses. Univariate and multivariate Cox regression analyses were performed to identify snoRNAs that are independently associated with the risk of mortality. Subsequently, a prognostic index (PI) for survival prediction was established, which may serve as a prognostic biomarker for patients with HCC (hazard ratio, 3.023; 95% confidence interval: 1.785‑5.119; P<0.001). In addition, a series of bioinformatics analyses were performed to identify potential differences in the perturbation of pathways between high‑xa0and low‑risk groups. The PI developed in the present study was determined to have a moderate predictive value regarding the clinical outcome for HCC patients.