Polymorphisms of CCNB1 Associated With the Clinical Outcomes of Platinum-Based Chemotherapy in Chinese NSCLC Patients

CCNB1 is involved in bladder cancer pathogenesis and silencing CCNB1 decelerates tumor growth and improves prognosis of bladder cancer

In search of an effective therapeutic target for bladder urothelial carcinoma (BLCA), the present study aimed to investigate the expression of cyclin B1 (CCNB1) and its putative mechanism in BLCA. BLCA sequencing data from Gene Expression Omnibus and The Cancer Genome Atlas were used to analyze expression of CCNB1 mRNA and high CCNB1 expression had a poorer prognosis compared with those with low expression. Immunohistochemistry (IHC) samples collected from the Human Protein Atlas database were analyzed for CCNB1 protein expression. Short hairpin (sh) CCNB1-transfected BLCA T24 and 5637 cells were used to investigate the effects of CCNB1 and inhibit the proliferation, migration and invasion of BLCA cells, affect the cell cycle distribution and promote apoptosis of 5637 cells. A sh-CCNB1 BLCA chicken embryo chorioallantoic membrane (CAM) transplantation model was established to observe the impacts of sh-CCNB1 on the tumorigenesis of BLCA in vivo. Analysis of sequencing data showed that CCNB1 mRNA was significantly elevated in tumor and BLCA compared with normal tissues [standardized mean difference (SMD)=1.21; 95% CI: 0.26-2.15; I²=95.9%]. IHC indicated that CCNB1 protein was localized in the nucleus and cytoplasm and was significantly increased in BLCA tumor tissues. The in vitro tests demonstrated that proliferation of T24 and 5637 cells transfected with sh-CCNB1 was significantly inhibited and cell migration and invasion ability were significantly decreased. sh-CCNB1 decreased the percentage of T24 cells in G0/G1, 5637 cells in the G0/G1 phase and S phase and increased percentage of 5637 cells in the G2/M phase and increased early apoptosis of 5637 cells. The in vivo experiments demonstrated that the mass of transplanted tumors was significantly decreased compared with the control group following silencing of CCNB1. The present results suggested that CCNB1 was involve in the development and prognosis of BLCA and silencing of CCNB1 may be a promising targeted therapy for BLCA.

Integrated omics profiling and network pharmacology uncovers the prognostic genes and multi-targeted therapeutic bioactives to combat lung cancer

Non-small cell lung cancer (NSCLC) is the frequent subtype of lung cancer and the currently used treatment methods, diagnosis, and chemoresistance are relatively ineffective. Determining the pharmacological targets from active biomolecules of medicinal plants has become a frontiers era for biomedical research to develop novel therapies. In view of these scenarios, this pilot study, network pharmacology, cheminformatics, integrative omics, molecular docking and in vitro anti-cancer analysis were performed to unveil the multi-targeted treatment mechanisms of novel plant bioactives to treat lung cancer. Bioactive molecules from medicinal plants were compiled from PubChem. Network pharmacology approach revealed that 29 compounds efficiently target the 390 human and lung cancer associated genes. In addition, comparative analysis was performed and identified the 7 bioactive molecules significantly targeting 8 lung cancer genes. The integrative omics analysis discovered unique genes between the lung cancer and normal lung tissues. These genes were further validated through protein-protein interaction, gene ontology, gene functional and pathway enrichment, boxplot and overall survival analyses to understand the function of unique genes and their involvement in cancer signaling pathways. Survival heatmap analyses identified the significant prognostic genes. Docking results revealed that, lupeol and p-coumaric acid displayed high binding affinities with MIF, CCNB1, FABP4. Hence, we selected these two bioactives for in vitro analysis. Furthermore, these selected bioactives were showed concentration dependent cytotoxicity against the lung adenocarcinoma cells (A549). This holistic study has opened up novel avenues and unravels the cancer prognostic genes which could serve as druggable target and bioactives with anti-cancerous efficacy. Further functional validations are prerequisites to deciphering these bioactives as commercial drug candidates.

Nanoparticles for local delivery of siRNA in lung therapy

An overview of the application of natural and synthetic, non-viral vectors for oligonucleotide delivery into the lung is presented in this review, with a special focus on lung cancer. Due to the specificity of the respiratory tract, its structure and natural barriers, the administration of drugs (especially those based on nucleic acids) is a particular challenge. Among widely tested non-viral drug and oligonucleotides carriers, synthetic polymers seem to be most promising. Unique properties of these nanoparticles allow for essentially unlimited possibilities regarding their design and modification. This gives hope that optimal nanoparticles with ideal nucleic acid carrier properties for lung cancer therapy will eventually emanate.

Impact of genetic factors on platinum-induced gastrointestinal toxicity

Severe gastrointestinal (GI) toxicity is a common side effect after platinum-based chemotherapy. The incidence and severity of GI toxicity vary among patients with the same chemotherapy. Genetic factors involved in platinum transport, metabolism, detoxification, DNA repair, cell cycle control, and apoptosis pathways may account for the interindividual difference in GI toxicity. The influence of gene polymorphisms in the platinum pathway on GI toxicity has been extensively analyzed. Variations in study sample size, ethnicity, design, treatment schedule, dosing, endpoint definition, and assessment of toxicity make it difficult to precisely interpret the results. Hence, we conducted a review to summarize the most recent pharmacogenomics studies of GI toxicity in platinum-based chemotherapy and identify the most promising avenues for further research.

Comprehensive transcriptomic analysis identifies novel regulators of lung adenocarcinoma

Lung adenocarcinoma (LA) is a subtype of lung cancer that accounts for about 40% of all lung cancers. Analysis of molecular mechanisms controlling this cancer can help scientists to detect, control and treat LA. Here, a microarray dataset (GSE118370) containing six normal lung (NL) and six LA samples was screened using GEO2R to find differentially expressed genes (DEGs). Then, DAVID, KEGG and ChEA were used to analyze DEGs-related gene ontology, pathways and transcription factors (TFs), respectively. The Protein-protein interaction network for DEGs and TFs was constructed by STRING and Cytoscape. To find microRNAs and metabolites associated with DEGs, miRTarBase and HMDB were used, respectively. It was found that 350 genes were upregulated and 608 genes were downregulated in LA. The upregulated genes or LA-related gens were enriched in biological process and pathways such as extracellular matrix disassembly and p53 signaling pathway, whereas the downregulated genes or NL-related genes were enriched in cell adhesion and cell-surface receptor signaling pathway. ESR1, KIF18B, BIRC5, CHEK1, CCNB1 and AURKA were determined as hub genes for LA. FOXA1 and TFAP2A had the highest number of connectivity in LA-related TFs. hsa-miR-192-5p and hsa-miR-215-5p could target the highest number of LA-related genes. Metabolite analysis showed that Estrone and NADPH were among the top ten metabolites associated with LA-related genes. Taken together, LA-related genes, especially the hub genes, TFs, and metabolites might be used as novel markers for LA, as well as for diagnosis and guiding therapeutic strategies of LA.

Efficacy and safety of S-1 maintenance therapy in advanced non-small-cell lung cancer patients

BACKGROUND

Previous reports have demonstrated that S-1 has remarkable effects in the maintenance treatment of advanced non-small-cell lung cancer (NSCLC), and has less toxic and side effects than conventional drugs.

AIM

To investigate the efficacy and safety of S-1 maintenance therapy in patients with advanced NSCLC.

METHODS

Ninety-four patients with NSCLC admitted to our hospital from September 2015 to April 2018 were included in the study and divided into the S-1 group (47 cases) and the gemcitabine group (47 cases) by random digital table method. The S-1 group was treated with S-1, while the gemcitabine group received gemcitabine treatment. The clinical efficacy and quality of life of the patients after treatment in the two groups were evaluated.

RESULTS

There was no significant difference in the total effectiveness rate between the two groups (P = 0.519). The quality-of-life scores indicated that there was no significant difference between the two groups in terms of four dimensions of the GQOLI-74 questionnaire (P = 0.518, 0.094, 0.338, 0.418). The incidence of nausea and vomiting, granulocytopenia and diarrhea in the S-1  group was significantly lower than that in the gemcitabine group (P = 0.001, 0.001 and 0.001, respectively). There was no significant difference in the incidence of thrombocytopenia (P = 0.366), the progression-free survival (P = 0.064), and the survival between the two groups (P = 0.050).

CONCLUSION

S-1 maintenance therapy shows a significant therapeutic effect in patients with advanced NSCLC. It has the same clinical efficacy as gemcitabine, but with less toxic and side effects than conventional drugs.

Identification of Hub Genes as Biomarkers Correlated with the Proliferation and Prognosis in Lung Cancer: A Weighted Gene Co-Expression Network Analysis

Lung cancer is one of the most malignant tumors in the world. Early diagnosis and treatment of lung cancer are vitally important to reduce the mortality of lung cancer patients. In the present study, we attempt to identify the candidate biomarkers for lung cancer by weighted gene co-expression network analysis (WGCNA). Gene expression profile of GSE30219 was downloaded from the gene expression omnibus (GEO) database. The differentially expressed genes (DEGs) were analyzed by the limma package, and the co-expression modules of genes were built by WGCNA. UALCAN was used to analyze the relative expression of normal group and tumor subgroups based on tumor individual cancer stages. Survival analysis for the hub genes was performed by Kaplan–Meier plotter analysis with the TCGA database. A total of 2176 genes (745 upregulated and 1431 downregulated genes) were obtained from the GSE30219 database. Seven gene co-expression modules were conducted by WGCNA and the blue module might be inferred as the most crucial module in the pathogenesis of lung cancer. In the pathway enrichment analysis of KEGG, the candidate genes were enriched in the “DNA replication,” “Cell cycle,” and “P53 signaling pathway” pathways. Among these, the cell cycle pathway was the most significant pathway in the blue module with four hub genes CCNB1, CCNE2, MCM7, and PCNA which were selected in our study. Kaplan–Meier plotter analysis indicated that the high expressions of four hub genes were correlated with a worse overall survival (OS) and advanced tumors. qRT-PCR showed that mRNA expression levels of MCM7 (p = 0.038) and CCNE2 (0.003) were significantly higher in patients with the TNM stage. In summary, the high expression of the MCM7 and CCNE2 were significantly related with advanced tumors and worse OS in lung cancer. Thus, the MCM7 and CCNE2 genes can be good indicators for cellular proliferation and prognosis in lung cancer.

Determination of Endothelial Nitric Oxide Synthase Gene Polymorphism and Plasma Asymmetric Dimethyl Arginine Concentrations in Patients with Lung Cancer

Objective

Genetic factors can contribute to both the occurrence and development of lung cancer. This study aimed to investigate endothelial nitric oxide synthase (eNOS) G894T and T-786C polymorphisms and plasma asymmetric dimethylarginine (ADMA) levels of lung cancer patients in comparison with healthy subjects.

Materials and Methods

A total of 200 subjects, 100 patients with lung cancer and 100 healthy volunteers were included in this study. To determine eNOS gene polymorphisms, we collected and analyzed blood samples with polymerase chain reaction (PCR). Plasma ADMA levels were evaluated by high-performance liquid chromatography (HPLC).

Results

The difference in gene polymorphisms between lung cancer patients and healthy controls were insignificant. However, lung cancer patients had statistically significantly higher plasma ADMA levels than healthy controls. The patients and control groups with CC polymorphisms and TT polymorphisms on eNOS T-786C and G894T gene regions had higher plasma ADMA levels. The CC polymorphisms and plasma ADMA levels were higher in patients with small-cell lung cancer compared to those in patients with non-small-cell lung cancer.

Conclusion

Although eNOS gene polymorphisms had no significant difference between lung cancer patients and healthy controls, plasma ADMA levels were higher in lung cancer patients compared to healthy controls. Our study suggests that CC genotypes and elevated plasma ADMA levels might be associated with small-cell lung cancer.

Bioinformatics analysis and verification of gene targets for benign tracheal stenosis

Background

Tracheal injury could cause intratracheal scar hyperplasia which in turn causes benign tracheal stenosis (TS). With the increasing use of mechanical ventilation and ventilator, the incidence of TS is increasing. However, the molecular mechanisms of TS have not been elucidated. It is significant to further explore the molecular mechanisms of TS.

Methods

The repeatability of public data was verified. Differently expressed genes (DEGs) and most significant genes were identified between TS and normal samples. Enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were analyzed. The comparative toxicogenomics database were analyzed. TS patients were recruited and RT‐qPCR were performed to verify the most significant genes.

Results

There exist strong correlations among samples of TS and normal group. There was a total of 194 DEGs, including 61 downregulated DEGs and 133 upregulated DEGs. GO were significantly enriched in mitotic nuclear division, cell cycle, and cell division. Analysis of KEGG indicated that the top pathways were cell cycle, and p53 pathway. MKI67(OMIM:176741), CCNB1(OMIM:123836), and CCNB2(OMIM:602755) were identified as the most significant genes of TS, and validated by the clinical samples.

Conclusion

Bioinformatics methods might be useful method to explore the mechanisms of TS. In addition, MKI67, CCNB1, and CCNB2 might be the most significant genes of TS.

Competitive endogenous RNA network identifies four long non-coding RNA signature as a candidate prognostic biomarker for lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is the most commonly histological subtype of lung cancer (LC) and the prognoses of the majority of LUAD patients are still very poor. The present study aimed at integrating long non-coding RNA (lncRNA), microRNA (miRNA) and messenger RNA (mRNA) expression data to construct lncRNA-miRNA-mRNA competitive endogenous RNA (ceRNA) network and identify importantly potential lncRNA signature in ceRNA network as a candidate prognostic biomarker for LUAD patients.

METHODS

lncRNA, miRNA and mRNA expression data as well as clinical characteristics of LUAD patients were retrieved from The Cancer Genome Atlas (TCGA) database. Differentially expressed lncRNAs (DElncRNAs), differentially expressed mRNAs (DEmRNAs) and differentially expressed miRNA (DEmiRNA) between LUAD and normal lung tissues samples were analyzed. A lncRNA-miRNA-mRNA ceRNA network was constructed and the biological functions of DEmRNAs in ceRNA network were analyzed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Univariate and multivariate Cox regression analyses of DElncRNAs in ceRNA network were implemented to predict the overall survival (OS) in LUAD patients. The receiver operating characteristic (ROC) analysis was used to evaluate the performance of multivariate Cox regression model.

RESULTS

A total of 1,664 DElncRNAs, 120 DEmiRNAs and 2,503 DEmRNAs was identified between LUAD and normal lung tissues samples. A lncRNA-miRNA-mRNA ceRNA network including 140 DElncRNAs, 33 DEmiRNAs and 57 DEmRNAs was established. Kaplan-Meier (KM) [Log-rank (LR) test] and univariate regression analysis of those 140 DElncRNAs revealed that 7 DElncRNAs (LINC00518, UCA1, NAV2-AS2, MED4-AS1, SYNPR-AS1, AC011483.1, AP002478.1) were simultaneously identified to be associated with OS of LUAD patients. A multivariate Cox regression analysis of those 7 DElncRNAs showed that a group of 4 DElncRNAs including AP002478.1 (Cox P=4.66E-03), LINC00518 (Cox P=2.34E-04), MED4-AS1 (Cox P=6.42E-03) and NAV2-AS2 (Cox P=6.66E-02) had significantly prognostic value in OS of LUAD patients. The cumulative risk score indicated that the 4-lncRNA signature was significantly associated with OS of LUAD patients (P=0). The area under the curve (AUC) of the 4-lncRNA signature related with 3-year survival was 0.669.

CONCLUSIONS

The present study provides novel insights into the lncRNA-related regulatory mechanisms in LUAD, and identifying 4-lncRNA signature may serve as a candidate prognostic biomarker in predicting the OS of LUAD patients.

Bioinformatics analysis of key differentially expressed genes in well and poorly differentiated endometrial carcinoma

Endometrial carcinoma (EC) is one of the most common gynecological malignancies. The malignant degree increases between grade (G)1 and G3, and EC of G3 usually presents a high recurrence rate and poor prognosis. Therefore, the present study aimed to examine the principal genes associated with the degree of differentiation in EC. The microarrays GSE17025, GSE24537 and GSE35784, representing data of Type I EC samples of G1 and G3, were downloaded from the Gene Expression Omnibus. The differentially expressed genes (DEGs) and differentially expressed micro (mi)RNAs (DEMs) were identified, followed by functional enrichment analyses and interaction network construction. In total, 83 upregulated and 130 downregulated DEGs with the same expression trends in two mRNA datasets were screened. The upregulated DEGs were primarily enriched in 'mitotic cell cycle process', 'cell cycle process' and 'mitotic cell cycle'; while the downregulated DEGs were enriched in 'cellular component assembly involved in morphogenesis', 'cell projection organization' and 'microtubule‑based movement'. From the protein‑protein interaction network, DNA topoisomerase IIα, kinesin family member 11, cyclin B1 and BUB1 mitotic checkpoint serine/threonine were identified as foremost hub genes. One module was extracted and involved in 'mitotic cell cycle process' and 'cell cycle process'. Based on the analysis of DEMs and the miRNA‑target regulatory network, miRNA‑9 may be the most important upregulated DEM, and the DEGs forkhead box P1 and cyclin E1 may serve vital roles in the differentiation of EC. In conclusion, principal genes were identified that may be determinants of the carcinogenesis of poorly differentiated EC, which may facilitate the examination of potential molecular mechanisms. These genes may additionally help identify candidate biomarkers and novel therapeutic targets for poorly differentiated EC.

Upregulation of BUB1B, CCNB1, CDC7, CDC20, and MCM3 in Tumor Tissues Predicted Worse Overall Survival and Disease-Free Survival in Hepatocellular Carcinoma Patients

OBJECTIVE

To evaluate the association between upregulated differentially expressed genes (DEGs) and the outcomes of patients with hepatocellular carcinoma (HCC).

METHODS

Using Gene Expression Omnibus (GEO) datasets including GSE45436, GSE55092, GSE60502, GSE84402, and GSE17548, we detected upregulated DEGs in tumors. KEGG, GO, and Reactome enrichment analysis of the DEGs was conducted to clarify their function. The impact of the upregulated DEGs on patients' survival was analyzed based on TCGA profile.

RESULTS

161 shared upregulated DEGs were identified among GSE45436, GSE55092, GSE60502, and GSE84402 profiles. Cell cycle was the shared pathway/biological process in the gene sets investigation among databases of KEGG, GO, and Reactome. After being validated in GSE17548, 13 genes including BUB1B, CCNA2, CCNB1, CCNE2, CDC20, CDC6, CDC7, CDK1, CDK4, CDKN2A, CHEK1, MAD2L1, and MCM3 in cell cycle pathway were shared in the three databases for enrichment. The expression of BUB1B, CCNB1, CDC7, CDC20, and MCM3 was upregulated in HCC tissues when compared with adjacent normal tissues in 6.67%, 7.5%, 8.06%, 5.56%, and 9.72% of HCC patients, respectively. Overexpression of BUB1B, CCNB1, CDC7, CDC20, and MCM3 in HCC tissues accounted for poorer overall survival (OS) and disease-free survival (DFS) in HCC patients (all log rank P < 0.05). BUB1B, CCNB1, CDC7, CDC20, and MCM3 were all overexpressed in HCC patients with neoplasm histologic grade G3-4 compared to those with G1-2 (all P < 0.05). BUB1B, CCNB1, and CDC20 were significantly upregulated in HCC patients with vascular invasion (all P < 0.05). Additionally, levels of BUB1B, CCNB1, CDC7, and CDC20 were significantly higher in HCC patients deceased, recurred, or progressed (all P < 0.05).

CONCLUSION

Correlated with advanced histologic grade and/or vascular invasion, upregulation of BUB1B, CCNB1, CDC7, CDC20, and MCM3 in HCC tissues predicted worse OS and DFS in HCC patients. These genes could be novel therapeutic targets for HCC treatment.