Downregulation of BIRC5 inhibits the migration and invasion of esophageal cancer cells by interacting with the PI3K/Akt signaling pathway

Crocin enhances the sensitivity to paclitaxel in human breast cancer cells by reducing BIRC5 expression

Paclitaxel (PTX) is one of the first-line chemotherapeutic agents for treating breast cancer. However, PTX resistance remains a major hurdle in breast cancer therapy. Crocin, the main chemical constituent of saffron, shows anti-cancer activity against various types of cancer. However, the effect of crocin on the resistance of PTX in breast cancer is still unknown. CCK-8 and TUNEL assays were employed to detect cell viability and apoptosis, respectively. The targets of crocin were predicted using HERB database and the targets associated with breast cancer were acquired using GEPIA database. The Venn diagram was utilized to identify the common targets between crocin and breast cancer. Baculoviral inhibitor of apoptosis repeat containing 5 (BIRC5) expression was detected by qRT-PCR and western blot analysis. The correlation between BIRC5 expression and survival was analyzed by Kaplan-Meier plotter and PrognoScan databases. Our data suggested that crocin aggravated PTX-induced decrease of viability and increase of apoptosis in MCF-7 and MCF-7/PTX cells. BIRC5 was identified as the target of crocin against breast cancer. Crocin inhibited BIRC5 expression in MCF-7 and MCF-7/PTX cells. BIRC5 is overexpressed in breast cancer tissues, as well as PTX-sensitive and PTX-resistant breast cancer cells. BIRC5 expression is related to the poor survival of patients with breast cancer. Depletion of BIRC5 strengthened PTX-induced viability reduction and promotion of apoptosis in MCF-7 and MCF-7/PTX cells. Moreover, BIRC5 overexpression reversed the inhibitory effect of crocin on PTX resistance in breast cancer cells. In conclusion, crocin enhanced the sensitivity of PTX in breast cancer cells partially through inhibiting BIRC5 expression.

CDC20 is a potential target gene to inhibit the tumorigenesis of MDCK cells

MDCK is currently the main cell line used for influenza vaccine production in culture. Previous studies have reported that MDCK cells possess tumorigenic ability in nude mice. Although complete cell lysis can be ensured during vaccine production, host cell DNA released after cell lysis may still pose a risk for tumorigenesis. Greater caution is needed in the production of human vaccines; therefore, the use of gene editing to establish cells incapable of forming tumors may significantly improve the safety of influenza vaccines. Knowledge regarding the genes and molecular mechanisms that affect the tumorigenic ability of MDCK cells is crucial; however, our understanding remains superficial. Through monoclonal cell screening, we previously obtained a cell line, CL23, that possesses significantly reduced cell proliferation, migration, and invasion abilities, and tumor-bearing experiments in nude mice showed the absence of tumorigenic cells. With a view to exploring tumorigenesis-related genes in MDCK cells, DIA proteomics was used to compare the differences in protein expression between wild-type (M60) and non-tumorigenic (CL23) cells. Differentially expressed proteins were verified at the mRNA level by RT-qPCR, and a number of genes involved in cell tumorigenesis were preliminarily screened. Immunoblotting further confirmed that related protein expression was significantly reduced in non-tumorigenic cells. Inhibition of CDC20 expression by RNAi significantly reduced the proliferation and migration of MDCK cells and increased the proliferation of the influenza virus; therefore, CDC20 was preliminarily determined to be an effective target gene for the inhibition of cell tumorigenicity. These results contribute to a more comprehensive understanding of the mechanism underlying cell tumorigenesis and provide a basis for the establishment of target gene screening in genetically engineered non-tumorigenic MDCK cell lines.

Ginsenoside Rg3, a promising agent for NSCLC patients in the pandemic: a large-scale data mining and systemic biological analysis

Introduction

Non-small cell lung cancer (NSCLC) patients are particularly vulnerable to the Coronavirus Disease-2019 (COVID-19). Currently, no anti-NSCLC/COVID-19 treatment options are available. As ginsenoside Rg3 is beneficial to NSCLC patients and has been identified as an entry inhibitor of the virus, this study aims to explore underlying pharmacological mechanisms of ginsenoside Rg3 for the treatment of NSCLC patients with COVID-19.

Methods

Based on a large-scale data mining and systemic biological analysis, this study investigated target genes, biological processes, pharmacological mechanisms, and underlying immune implications of ginsenoside Rg3 for NSCLC patients with COVID-19.

Results

An important gene set containing 26 target genes was built. Target genes with significant prognostic value were identified, including baculoviral IAP repeat containing 5 (BIRC5), carbonic anhydrase 9 (CA9), endothelin receptor type B (EDNRB), glucagon receptor (GCGR), interleukin 2 (IL2), peptidyl arginine deiminase 4 (PADI4), and solute carrier organic anion transporter family member 1B1 (SLCO1B1). The expression of target genes was significantly correlated with the infiltration level of macrophages, eosinophils, natural killer cells, and T lymphocytes. Ginsenoside Rg3 may benefit NSCLC patients with COVID-19 by regulating signaling pathways primarily involved in anti-inflammation, immunomodulation, cell cycle, cell fate, carcinogenesis, and hemodynamics.

Conclusions

This study provided a comprehensive strategy for drug discovery in NSCLC and COVID-19 based on systemic biology approaches. Ginsenoside Rg3 may be a prospective drug for NSCLC patients with COVID-19. Future studies are needed to determine the value of ginsenoside Rg3 for NSCLC patients with COVID-19.

The Prognostic and Therapeutic Implications of the Chemoresistance Gene BIRC5 in Triple-Negative Breast Cancer

Chemoresistance affects TNBC patient treatment responses. Therefore, identifying the chemoresistant gene provides a new approach to understanding chemoresistance in TNBC. BIRC5 was examined in the current study as a tool for predicting the prognosis of TNBC patients and assisting in developing alternative therapies using online database tools. According to the examined studies, BIRC5 was highly expressed in 45 to 90% of TNBC patients. BIRC5 is not only abundantly expressed but also contributes to resistance to chemotherapy, anti-HER2 therapy, and radiotherapy. Patients with increased expression of BIRC5 had a median survival of 31.2 months compared to 85.8 months in low-expression counterparts (HR, 1.73; CI, 1.4−2.13; p = 2.5 × 10−7). The overall survival, disease-free survival, relapse-free survival, distant metastasis-free survival, and the complete pathological response of TNBC patients with high expression of BIRC5 who received any chemotherapy (Taxane, Ixabepilone, FAC, CMF, FEC, Anthracycline) and anti-HER2 therapy (Trastuzumab, Lapatinib) did not differ significantly from those patients receiving any other treatment. Data obtained indicate that the BIRC5 promoter region was substantially methylated, and hypermethylation was associated with higher BIRC5 mRNA expression (p < 0.05). The findings of this study outline the role of BIRC5 in chemotherapy-induced resistance of TNBC, further indicating that BIRC5 may serve as a promising prognostic biomarker that contributes to chemoresistance and could be a possible therapeutic target. Meanwhile, several in vitro studies show that flavonoids were highly effective in inhibiting BIRC5 in genetically diverse TNBC cells. Therefore, flavonoids would be a promising strategy for preventing and treating TNBC patients with the BIRC5 molecule.

Development and Validation of an Autophagy-Related Gene Signature for Predicting the Prognosis of Hepatocellular Carcinoma

Purpose

Autophagy is a lysosomal degradation pathway that is essential for maintaining the homeostasis of the intracellular environment. Mounting evidence indicates that autophagy plays an essential role in the occurrence and development of hepatocellular cancer (HCC). This research is aimed at exploring the prognostic value of autophagy-related genes (ARGs) in HCC patients.

Methods

The Wilcoxon test was used to identify differentially expressed ARGs in The Cancer Genome Atlas (TCGA) HCC cohort. Then, the TCGA cohort was randomly divided into training and testing groups. Cox and LASSO regression models were used to screen for autophagy-related genes that affect overall survival (OS) in the TCGA training group. Based on the coefficient of risk genes, we constructed an autophagy-related gene signature for predicting the prognosis of HCC patients. Finally, we validated the prognostic significance of autophagy-related gene signature using the TCGA testing group and three external datasets.

Results

ATG10, BIRC5, GAPDH, and TMEM74 are risk genes for OS. According to the optimal cutoff value of risk score in each HCC dataset, HCC patients can divide into high- and low-risk groups. ARG risk score can significantly distinguish HCC patients with different survival outcomes. Meanwhile, the ARG risk score is independently correlated with OS in multiple HCC cohorts.

Conclusions

The autophagy-related risk score can effectively screen high-risk HCC patients and provide guidance for clinical prevention and treatment of HCC.

Identification of Circular RNAs Related to Vascular Endothelial Proliferation, Migration, and Angiogenesis After Spinal Cord Injury Using Microarray Analysis in Female Mice

Background: Traumatic spinal cord injury (SCI) can result in severe disability and causes a considerable socio-economic burden worldwide. Circular RNAs (circRNAs) are important regulators of gene expression and pathological processes, and may represent therapeutic targets for SCI. To further evaluate the role of circRNAs in SCI, we elucidated circRNA expression profiles related to vascular endothelial proliferation, migration, and angiogenesis during the early stages of secondary injury in a mouse model of SCI.

Methods: Microarray analysis was performed to investigate the circRNA expression patterns in the spinal cord 3 days after SCI in female mice. Bioinformatic analyses, including GO enrichment analysis, KEGG pathway analysis, and circRNA-miRNA-mRNA network construction, were conducted to explore the role of circRNA dysregulation in vascular endothelial proliferation, migration, and angiogenesis following SCI.

Results: The expression of 1,288 circRNAs was altered (>2-fold change, p < 0.05) in the spinal cord after SCI, consisting of 991 upregulated and 297 downregulated circRNAs. We constructed a circRNA-mRNA network to predict whether these circRNAs could act as “miRNA sponges.” We next assessed the association of altered circRNAs with vascular endothelial proliferation, migration, and angiogenesis using GO and KEGG analyses. Using this analysis, we found that a total of 121 circRNAs were correlated with vascular endothelial proliferation, migration, and angiogenesis in the spinal cord after SCI.

Conclusions: Our study provides circRNA expression profiles during the early stages of SCI. circRNA.7079, circRNA.7078, and circRNA.6777 were found to play key roles in the vascular endothelial proliferation, migration, and angiogenesis, and may represent therapeutic targets for SCI.

Expression of Four Autophagy-Related Genes Accurately Predicts the Prognosis of Gastrointestinal Cancer in Asian Patients

Gastrointestinal (GI) cancers are among the most fatal diseases in the world. Numerous studies have demonstrated the relationship between autophagy and development of gastrointestinal cancers. However, whether autophagy-related genes can predict prognosis of GI cancers in individuals of Asian ancestry has not been defined. This study, evaluated the prognostic value of autophagy-related genes in gastrointestinal cancer. Expression profile of autophagy-related genes for 296 gastrointestinal cancer patients of Asian ancestry was downloaded from the TCGA database (TCGA-LIHC, TCGA-STAD, TCGA-ESCA, TCGA-PAAD, TCGA-COAD, TCGA-CHOL, and TCGA-READ). The prognostic value of the autophagy-related genes was evaluated using univariate Cox, LASSO, and multivariate Cox regression analyses. The risk score of the autophagy-related gene signature was calculated to assess its predictive prognostic value for GI cancers. Forty-seven differentially expressed autophagy-related genes, in Asian patients with gastrointestinal cancers, were identified. Of the 47 genes, 4 were associated with prognosis of GI cancer (SQSTM1, BIRC5, NRG3, and CXCR4). A prognostic model for GI cancer, based on the expression of the above 4 genes in the training set, showed that cancer patients were stratified into high-risk and low-risk groups (P < 0.05). The utility of the model for overall survival (OS) of GI cancer patients was consistent across the entire set, training set, and test set (entire set: P = 4.568 × 10⁻⁴; train set: P = 5.718 × 10⁻³; test set: P = 3.516 × 10⁻²). The sensitivity and specificity of the ROC curve of the above prognostic model in predicting the 5-year prognosis of GI cancer was satisfactory (entire set: 0.728; train set: 0.727; test set: 0.733). Analysis of clinical samples validated the overexpression of the 4 genes (SQSTM1, BIRC5, NRG3, and CXCR4) in tumor tissues relative to paired normal tissues, consistent with bioinformatic findings. Expression of the 4 autophagy-related genes (SQSTM1, BIRC5, NRG3, and CXCR4) can accurately predict the prognosis of gastrointestinal tumors in Asian patients.

Cancer Grade Model: a multi-gene machine learning-based risk classification for improving prognosis in breast cancer

BACKGROUND

Prognostic stratification of breast cancers remains a challenge to improve clinical decision making. We employ machine learning on breast cancer transcriptomics from multiple studies to link the expression of specific genes to histological grade and classify tumours into a more or less aggressive prognostic type.

MATERIALS AND METHODS

Microarray data of 5031 untreated breast tumours spanning 33 published datasets and corresponding clinical data were integrated. A machine learning model based on gradient boosted trees was trained on histological grade-1 and grade-3 samples. The resulting predictive model (Cancer Grade Model, CGM) was applied on samples of grade-2 and unknown-grade (3029) for prognostic risk classification.

RESULTS

A 70-gene signature for assessing clinical risk was identified and was shown to be 90% accurate when tested on known histological-grade samples. The predictive framework was validated through survival analysis and showed robust prognostic performance. CGM was cross-referenced with existing genomic tests and demonstrated the competitive predictive power of tumour risk.

CONCLUSIONS

CGM is able to classify tumours into better-defined prognostic categories without employing information on tumour size, stage, or subgroups. The model offers means to improve prognosis and support the clinical decision and precision treatments, thereby potentially contributing to preventing underdiagnosis of high-risk tumours and minimising over-treatment of low-risk disease.

Upregulation of BIRC5 plays essential role in esophageal squamous cell carcinoma

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is one of the most common cancers in the world, the detection and prognosis of which are still unsatisfactory. Thus, it is essential to explore the factors that may identify ESCC and evaluate the prognosis of ESCC patients.

RESULTS

Both protein and mRNA expression levels of BIRC5 are upregulated in ESCC group rather than non-ESCC group (standardized mean difference > 0). BIRC5 mRNA expression is related to the age, tumor location, lymph node stage and clinical stage of ESCC patients (p < 0.05). BIRC5 expression makes it feasible to distinguish ESCC from non-ESCC (area under the curve > 0.9), and its high expression is related to poor prognosis of ESCC patients (restrictive survival time difference = -0.036, p < 0.05). BIRC5 may play an important role in ESCC by influencing the cell cycle pathway, and CDK1, MAD2L and CDC20 may be the hub genes of this pathway. The transcription factors-MAZ and TFPD1 -are likely to regulate the transcription of BIRC5, which may be one of the factors for the high expression of BIRC5 in ESCC.

CONCLUSIONS

The current study shows that upregulation of BIRC5 may have essential clinical value in ESCC, and contributes to the understanding of the pathogenesis of ESCC.

The Early Diagnostic and Prognostic Value of BIRC5 in Clear-Cell Renal Cell Carcinoma Based on the Cancer Genome Atlas Data

PURPOSE

The aim of this study was to investigate the role of BIRC5 for early diagnosis and prognosis in clear-cell renal cell carcinoma (ccRCC) by studying the expression of BIRC5 and the correlation between BIRC5 expression and clinicopathological parameters and prognosis in ccRCC.

METHODS

The BIRC5 expression in ccRCC tissues and normal kidney tissues was measured using the Cancer Genome Atlas database and the Human Protein Atlas database. The correlation between BIRC5 expression and clinicopathological parameters and prognosis in ccRCC was analyzed using UALCAN, the Kaplan-Meier plotter, GEPIA, and SurvExpress. Thirteen-paired ccRCC plasma samples were used to verify the BIRC5 early diagnosis value of ccRCC.

RESULTS

The BIRC5 expression is significantly higher in ccRCC than in normal kidney tissues, and is correlated with the clinical stage and pathological grade of ccRCC (p < 0.05). The result of analyzing the relationship between BIRC5 expression and outcomes in ccRCC indicates that a high BIRC5 expression is an independent prognostic factor affecting the overall survival and disease-free survival of ccRCC (p < 0.05). Compared with normal kidney tissues, the immunohistochemical test shows that BIRC5 is significantly upregulated in ccRCC tissues. mRNA expression levels of BIRC5 were significantly higher in the ccRCC plasma than normal (p < 0.05).

CONCLUSIONS

The high expression of BIRC5 is an important indicator for the prognosis of ccRCC, which makes BIRC5 an effective biomarker for predicting the prognosis of patients in ccRCC. BIRC5 may be a great potential biomarker for early diagnosis of ccRCC.

BAI1 nuclear expression reflects the survival of nonsmoking non-small cell lung cancer patients

Background

Smoking‐ and nonsmoking‐associated lung cancers have different mechanisms of carcinogenesis. We divided non‐small cell lung cancer (NSCLC) patients into nonsmoking and smoking groups with the aim of trying to understand the utility of brain‐specific angiogenesis inhibitor 1 (BAI1) expression in the separate groups.

Methods

Clinicopathological data were obtained from 148 patients who had undergone surgery for NSCLC of the lung. Tissue microarray blocks were made of samples from NSCLC patients. Two pathologists graded the intensity of BAI1 expression as high or low expression in the cancer cells of patients in the smoking and nonsmoking groups.

Results

NSCLC nonsmokers with higher BAI1 nuclear expression had poor disease‐specific survival (DSS) (hazard ratio: 2.679; 95% confidence interval [CI]:1.022–7.022, p = 0.045). The Kaplan–Meier survival curve confirmed that higher BAI1 expression was significantly associated with poor DSS (p = 0.034) in the nonsmoking group.

Conclusions

We divided NSCLC patients into nonsmoking and smoking groups and found that nuclear BAI1 expression was related to patient survival in nonsmoking NSCLC patients. We suggest BAI1 expression as a predictive marker of nonsmoking‐associated NSCLC and recommend that it be evaluated as an AJCC staging criterion in the future.

Mining the plasma-proteome associated genes in patients with gastro-esophageal cancers for biomarker discovery

Gastro-esophageal (GE) cancers are one of the major causes of cancer-related death in the world. There is a need for novel biomarkers in the management of GE cancers, to yield predictive response to the available therapies. Our study aims to identify leading genes that are differentially regulated in patients with these cancers. We explored the expression data for those genes whose protein products can be detected in the plasma using the Cancer Genome Atlas to identify leading genes that are differentially regulated in patients with GE cancers. Our work predicted several candidates as potential biomarkers for distinct stages of GE cancers, including previously identified CST1, INHBA, STMN1, whose expression correlated with cancer recurrence, or resistance to adjuvant therapies or surgery. To define the predictive accuracy of these genes as possible biomarkers, we constructed a co-expression network and performed complex network analysis to measure the importance of the genes in terms of a ratio of closeness centrality (RCC). Furthermore, to measure the significance of these differentially regulated genes, we constructed an SVM classifier using machine learning approach and verified these genes by using receiver operator characteristic (ROC) curve as an evaluation metric. The area under the curve measure was > 0.9 for both the overexpressed and downregulated genes suggesting the potential use and reliability of these candidates as biomarkers. In summary, we identified leading differentially expressed genes in GE cancers that can be detected in the plasma proteome. These genes have potential to become diagnostic and therapeutic biomarkers for early detection of cancer, recurrence following surgery and for development of targeted treatment.

Identification of prognostic significance of BIRC5 in breast cancer using integrative bioinformatics analysis

Aims: Baculoviral inhibitor of apoptosis repeat containing 5 (BIRC5) plays vital roles in carcinogenesis by influencing cell division and proliferation and by inhibiting apoptosis. However, the prognostic significance of BIRC5 remains unclear in breast cancer.

Methods:BIRC5 expression and methylation status were evaluated using the Oncomine and The Cancer Genome Atlas (TCGA) databases. The relevance between BIRC5 and different clinicopathological features as well as survival information was analyzed using the bc-GenExMiner database and Kaplan–Meier Plotter. BIRC5–drug interaction network was obtained using the Comparative Toxicogenomics Database.

Results: Based on the results from databases and own hospital data, BIRC5 was higher expressed in different breast cancer subtypes compared with the matched normal individuals. Hormone receptors were negatively correlated with BIRC5 expression, whereas the Scarff–Bloom–Richardson (SBR) grade, Nottingham Prognostic Index (NPI), human epidermal growth factor receptor-2 (HER-2) status, basal-like status, and triple-negative status were positively related to BIRC5 level in breast cancer samples with respect to normal tissues. High BIRC5 expression was responsible for shorter relapse-free survival, worse overall survival, reduced distant metastasis free survival, and increased risk of metastatic relapse event. BIRC5–drug interaction network indicated that several common drugs could modulate BIRC5 expression. Furthermore, a positive correlation between BIRC5 andcell-division cycle protein 20 (CDC20) gene was confirmed.

Conclusion:BIRC5 may be adopted as a promising predictive marker and potential therapeutic target in breast cancer. Further large-scale studies are needed to more precisely confirm the value of BIRC5 in treatment of breast cancer.

Endothelial YAP/TAZ Signaling in Angiogenesis and Tumor Vasculature

Solid tumors are dependent on vascularization for their growth. The hypoxic, stiff, and pro-angiogenic tumor microenvironment induces angiogenesis, giving rise to an immature, proliferative, and permeable vasculature. The tumor vessels promote tumor metastasis and complicate delivery of anti-cancer therapies. In many types of tumors, YAP/TAZ activation is correlated with increased levels of angiogenesis. In addition, endothelial YAP/TAZ activation is important for the formation of new blood and lymphatic vessels during development. Oncogenic activation of YAP/TAZ in tumor cell growth and invasion has been studied in great detail, however the role of YAP/TAZ within the tumor endothelium remains insufficiently understood, which complicates therapeutic strategies aimed at targeting YAP/TAZ in cancer. Here, we overview the upstream signals from the tumor microenvironment that control endothelial YAP/TAZ activation and explore the role of their downstream targets in driving tumor angiogenesis. We further discuss the potential for anti-cancer treatments and vascular normalization strategies to improve tumor therapies.

Identification and validation of an autophagy-related long non-coding RNA signature as a prognostic biomarker for patients with lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is the most predominant pathological subtype of lung cancer, accounting for 40–70% of all lung cancer cases. Although significant improvements have been made in the screening, diagnosis, and precise management in recent years, the prognosis of LUAD remains bleak. This study aimed to investigate the prognostic significance of autophagy-related long non-coding RNAs (lncRNAs) and construct an autophagy-related lncRNA prognostic model in LUAD.

Methods

The gene expression data of LUAD patients were obtained from The Cancer Genome Atlas (TCGA) database. All autophagy-related genes were downloaded from the Human Autophagy Database (HADb). Spearman’s correlation test was exploited to identify potential autophagy-related lncRNAs. The multivariate Cox regression analysis was used to construct the prognostic signature, which divided LUAD patients into high-risk and low-risk groups. Subsequently, the receiver operating characteristic (ROC) curves were generated to assess the predictive ability of this prognostic model for overall survival (OS) in these individuals. Then, the Gene set enrichment analysis (GSEA) was conducted to execute pathway enrichment analysis. Finally, a multidimensional validation was exploited to verify our findings.

Results

A total of 1,144 autophagy-related lncRNAs were identified to construct the co-expression network via Spearman’s correlation test (|R²| >0.4 and P≤0.001). Ultimately, a 16 autophagy-related lncRNAs prognostic model was constructed, and the area under the ROC curve (AUC) was 0.775. The results of GSEA enrichment analysis showed that the genes in the high-risk group were mainly enriched in cell cycle and p53 signaling pathways. The results of the multidimensional database validation indicated that the expression level of BIRC5 was significantly correlated with the expression level of TMPO-AS1. Furthermore, both TMPO-AS1 and BIRC5 had a higher expression level in LUAD samples. LUAD patients with high expression levels of TMPO-AS1 and BIRC5 were correlated with advanced disease stage and poor OS.

Conclusions

In summary, our results suggested that the prognostic signature of the 16 autophagy-related lncRNAs has significant prognostic value for LUAD patients. Furthermore, TMPO-AS1 and BIRC5 are potential predictors and therapeutic targets in these individuals.

Esomeprazole affects the proliferation, metastasis, apoptosis and chemosensitivity of gastric cancer cells by regulating lncRNA/circRNA-miRNA-mRNA ceRNA networks

Recently, proton pump inhibitors have become a hot research topic in the field of cancer drug research. However, the specific anti-tumor effect and underlying mechanisms of esomeprazole (ESO) in gastric cancer (GC) have remained elusive. In the present study, the toxic effects of ESO on the GC cell line AGS were investigated. MTT assays confirmed that ESO inhibited the proliferation of AGS cells and significantly enhanced their chemosensitivity. Transwell assays were performed to determine the anti-metastatic effects of ESO in AGS cells. Flow cytometry demonstrated that ESO induced cell apoptosis and caused cell cycle arrest in the S and G2/M phases. Furthermore, the differential expression of 948 long non-coding RNAs (lncRNAs), 114 circular RNAs (circRNAs), 1,197 mRNAs and 199 microRNAs (miRNAs) was detected in AGS cells via microarray analysis and RNA-sequencing. The top 10 differently expressed genes were mostly located on chromosomes 10 and 19. In addition, Gene Ontology analysis indicated that the genes were accumulated in functional terms associated with DNA replication, the cell cycle and the apoptotic signaling pathway. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed a variety of significantly dysregulated signaling pathways and targets, including the EGFR tyrosine kinase inhibitor resistance pathway, forkhead box O signaling pathway, p53 signaling pathway and platinum drug resistance pathway. Subsequently, the interactions of microtubule-associated protein 2 (MAP2), homeodomain-interacting protein kinase 2 (HIPK2) and ankyrin 2 (ANK2) were noted in a competing endogenous RNA (ceRNA) network, which may be important targets of ESO, exerting an anti-tumor effect in AGS cells. Collectively, ESO affects the proliferation, metastasis, apoptosis and chemosensitivity of gastric cancer cells by regulating long non-coding RNA/circRNA-miRNA-mRNA ceRNA networks.

Seven immune-related genes prognostic power and correlation with tumor-infiltrating immune cells in hepatocellular carcinoma

Background

Given poor prognosis and the lack of efficient therapy for advanced hepatocellular carcinoma, immunotherapy has emerged as an increasingly important role. However, there were few reports on the correlation between immune‐related genes and HCC. The purpose of this study is to construct a novel immune‐related gene‐based prognostic signature for HCC and to explore the potential mechanisms.

Methods

We organized expression data of 374 HCC samples and 50 nontumor samples from TCGA database. A robust signature was constructed by Cox regression analysis based on the immune‐related genes, which were filtered by differential genes analysis and Cox regression analysis. Then, the correlation analysis between the signature and clinical characteristics was conducted. And the signature was validated in ICGC database. Furthermore, the relationships between immune cell infiltration and the signature were explored by bioinformatics analysis.

Results

Seven genes‐based model (Risk score = BIRC5 * 0.0238 + FOS * 0.0055 + DKK1 * 0.0085 + FGF13 * 0.3432 + IL11 * 0.0135 + IL17D * 0.0878 + SPP1 * 0.0003) was constructed eventually and it was proved to be an independent prognostic factor for HCC patients. The signature‐calculated risk scores were shown to be positively correlated with the infiltration of these five immune cells, including macrophages, neutrophils, CD8+T, dendritic, and B cells. And the results suggested that high amplication of BIRC5, FGF13, IL11, IL17D, and SPP1 were more likely correlated with immune cell infiltration. Finally, PPI network, TFs‐based regulatory network and gene enrichment plots were performed to show potential molecular mechanisms.

Conclusion

We construct a robust immune‐related gene‐based prognostic signature with seven genes and explore potential mechanisms about it, which may contribute to the immunotherapy research for HCC.

Identification of nine key genes by bioinformatics analysis for predicting poor prognosis in smoking-induced lung adenocarcinoma

Aim:

To screen and identify key genes related to the development of smoking-induced lung adenocarcinoma (LUAD).

Materials & methods:

We obtained data from the GEO chip dataset GSE31210. The differentially expressed genes were screened by GEO2R. The protein interaction network of differentially expressed genes was constructed by STRING and Cytoscape. Finally, core genes were screened. The overall survival time of patients with the core genes was analyzed by Kaplan–Meier method. Gene ontology and Kyoto encyclopedia of genes and genomes bioaccumulation was calculated by DAVID.

Results:

Functional enrichment analysis indicated that nine key genes were actively involved in the biological process of smoking-related LUAD.

Conclusion:

23 core genes and nine key genes among them were correlated with adverse prognosis of LUAD induced by smoking.

What is the impact of BIRC5 gene polymorphisms on urinary cancer susceptibility? Evidence from 9348 subjects

As a member of apoptosis inhibition gene family, baculoviral IAP repeat containing 5 (BIRC5) protein acts as a survival factor in oncology through multiple ways. There are huge inconsistent results between urinary cancer risk and BIRC5 polymorphisms, so we searched and documented all eligible articles to clear up the mystery with the help of meta-analysis. According to the inclusion and exclusion criteria, we performed an overall search in Web of Science, PubMed, Google Scholar, Medline, CNKI and Wanfang database with pre-set search strategy up to November 2019. Z-test was performed to determine the statistical difference by Odds ratios (ORs) and 95% confidence intervals (CIs). The stability of the pooled ORs was conducted by one-way sensitivity analyses, Begg's funnel plots and Egger's test were employed to access the potential publication bias. The relationship of polymorphisms and BIRC5 expression was exposed by in-silico analysis, as well as the effects to tumorigenesis and prognosis. Finally, we enrolled 19 case-control studies to conducted this meta-analysis. An upgrade risk in rs9904341 of BIRC5 were revealed to be associated with urinary cancer in allele contrast model (OR = 1.222, P = 0.012), homozygote contrast model (OR = 1.579, P = 0.0001) and recessive contrast model (OR = 1.433, P < 0.001), as well as rs2071214 polymorphism in the subgroup analysis of BCa in allele contrast model (OR = 1.362, P = 0.011) and recessive contrast model (OR = 1.417, P = 0.015). On the other hand, rs17878467 variant plays an important role in prevent the tumorigenicity of urinary cancer in allele contrast model (OR = 0.672, P = 0.009), heterozygote contrast model (OR = 0.585, P = 0.006) and dominant contrast model (OR = 0.595, P = 0.004). In conclusion, we found that BIRC5 rs9904341, rs2071214 polymorphisms might cause the increased risk of urinary cancer, while rs17878467 reduces risk.

Prognostic Value of BIRC5 in Lung Adenocarcinoma Lacking EGFR, KRAS, and ALK Mutations by Integrated Bioinformatics Analysis

Objective

This study was aimed at investigating the prognostic significance of Baculoviral IAP repeat containing 5 (BIRC5) in lung adenocarcinoma (LAD) lacking EGFR, KRAS, and ALK mutations (triple-negative (TN) adenocarcinomas).

Methods

The gene expression profiles were obtained from Gene Expression Omnibus (GEO). The identification of the differentially expressed genes (DEGs) was performed by GeneSpring GX. Gene set enrichment analysis (GSEA) was used to execute gene ontology function and pathway enrichment analysis. The protein interaction network was constructed by Cytoscape. The hub genes were extracted by MCODE and cytoHubba plugin from the network. Then, using BIRC5 as a candidate, the prognostic value in LAD and TN adenocarcinomas was verified by the Kaplan-Meier plotter and The Cancer Genome Atlas (TCGA) database, respectively. Finally, the mechanism of BIRC5 was predicted by a coexpressed network and enrichment analysis.

Results

A total of 38 upregulated genes and 121 downregulated genes were identified. 9 hub genes were extracted. Among them, the mRNA expression of 5 genes, namely, BIRC5, MCM4, CDC20, KIAA0101, and TRIP13, were significantly upregulated among TN adenocarcinomas (all P < 0.05). Notably, only the overexpression of BIRC5 was associated with unfavorable overall survival (OS) in TN adenocarcinomas (log rank P = 0.0037). TN adenocarcinoma patients in the BIRC5 high-expression group suffered from a significantly high risk of distant metastasis (P = 0.046), advanced N stage (P = 0.033), and tumor-bearing (P = 0.031) and deceased status (P = 0.003). The mechanism of BIRC5 and coexpressed genes may be linked closely with the cell cycle.

Conclusion

Overexpressed in tumors, BIRC5 is associated with unfavorable overall survival in TN adenocarcinomas. BIRC5 is a potential predictor and therapeutic target in TN adenocarcinomas.