Targeting DTL induces cell cycle arrest and senescence and suppresses cell growth and colony formation through TPX2 inhibition in human hepatocellular carcinoma cells

Osteopontin regulates the growth and invasion of liver cancer cells via DTL

Osteopontin (OPN), a secreted phosphoglycoprotein, has important roles in tumor growth, invasion and metastasis in numerous types of cancers. Denticleless E3 ubiquitin protein ligase homolog (DTL), one of the CUL4-DDB1-associated factors (DCAFs), has also been associated with the invasion and metastasis of cancer cells. In the present study, OPN was found to induce DTL expression in liver cancer cells, and the results obtained using luciferase activity assays demonstrated that OPN could transcriptionally activate DTL expression in liver cancer cells. Furthermore, the results of the present study demonstrated that OPN could increase the expression of DTL via PI3K/AKT signaling. In conclusion, the present study demonstrated that OPN, as an extracellular matrix protein, is able to promote the growth and invasion of liver cancer cells through stimulation of the expression of DTL via the PI3K/AKT signaling pathway.

Pulse-SILAC and Interactomics Reveal Distinct DDB1-CUL4-Associated Factors, Cellular Functions, and Protein Substrates

Cullin-RING finger ligases represent the largest family of ubiquitin ligases. They are responsible for the ubiquitination of ∼20% of cellular proteins degraded through the proteasome, by catalyzing the transfer of E2-loaded ubiquitin to a substrate. Seven cullins are described in vertebrates. Among them, cullin 4 (CUL4) associates with DNA damage-binding protein 1 (DDB1) to form the CUL4-DDB1 ubiquitin ligase complex, which is involved in protein ubiquitination and in the regulation of many cellular processes. Substrate recognition adaptors named DDB1/CUL4-associated factors (DCAFs) mediate the specificity of CUL4-DDB1 and have a short structural motif of approximately forty amino acids terminating in tryptophan (W)-aspartic acid (D) dipeptide, called the WD40 domain. Using different approaches (bioinformatics/structural analyses), independent studies suggested that at least sixty WD40-containing proteins could act as adaptors for the DDB1/CUL4 complex. To better define this association and classification, the interaction of each DCAFs with DDB1 was determined, and new partners and potential substrates were identified. Using BioID and affinity purification-mass spectrometry approaches, we demonstrated that seven WD40 proteins can be considered DCAFs with a high confidence level. Identifying protein interactions does not always lead to identifying protein substrates for E3-ubiquitin ligases, so we measured changes in protein stability or degradation by pulse-stable isotope labeling with amino acids in cell culture to identify changes in protein degradation, following the expression of each DCAF. In conclusion, these results provide new insights into the roles of DCAFs in regulating the activity of the DDB1-CUL4 complex, in protein targeting, and characterized the cellular processes involved.

Pan-cancer analysis and experimental validation of DTL as a potential diagnosis, prognosis and immunotherapy biomarker

BACKGROUND

DTL has been found to be related with multiple cancers. However, comprehensive analyses, which identify the prediction value of DTL in diagnosis, prognosis, immune infiltration and treatment, have rarely been reported so far.

METHODS

Combined with the data online databases, the gene expression, gene mutation, function enrichment and the correlations with the immunity status and clinical indexes of DTL were analyzed. Expression of DTL and the degree of immune cell infiltration were examined by immunofluorescence (IF) and immunohistochemistry (IHC) and analyzed by statistical analysis. Furthermore, the influences of DTL on the cell cycle, cell proliferation and apoptosis were detected by live cell imaging, IF and flow cytometric (FC) analysis. Genomic stability assays were conducted by chromosome slide preparation.

RESULTS

DTL was widely expressed in various cells and tissues, while it was overexpressed in tumor tissues except acute myeloid leukemia (LAML). Pan-cancer bioinformatics analysis showed that the expression of DTL was correlated with the prognosis, immunotherapy, and clinical indexes in various cancers. In addition, gene set enrichment analysis (GSEA) uncovered that DTL was enriched in oocyte meiosis, pyrimidine metabolism, the cell cycle, the G2M checkpoint, mTORC1 signaling and E2F targets. Furthermore, the overexpression of DTL, and its association with immune cell infiltration and clinical indexes in liver hepatocellular carcinoma (LIHC), bladder urothelial carcinoma (BLCA) and stomach adenocarcinoma (STAD) were verified in our study. It was also verified that overexpression of DTL could regulate the cell cycle, promote cell proliferation and cause genomic instability in cultured cells, which may be the reason why DTL plays a role in the occurrence, progression and treatment of cancer.

CONCLUSIONS

Collectively, this study suggested that DTL is of clinical value in the diagnosis, prognosis and treatment of various cancers, and may be a potential biomarker in certain cancers.

Optimizing component formula suppresses lung cancer by blocking DTL-mediated PDCD4 ubiquitination to regulate the MAPK/JNK pathway

ETHNOPHARMACOLOGICAL RELEVANCE

Salvia miltiorrhiza Bunge and Panax ginseng C. A. Meyer have special curative effect on cancer treatment. The optimizing component formula (OCF) extracted from those two herbs was in line with the anti-lung cancer treatment principle of activating blood and supplementing 'Qi'. However, the study on the mechanism of component formula has always been an insurmountable challenge. Nowadays, the application of network pharmacology and artificial intelligence (AI) in the field of TCM provides new ideas for the study of new targets and mechanisms of TCM, which promotes the modernization of TCM.

AIM OF THE STUDY

This study aims to further explore the anti-lung cancer mechanism of OCF by using an integrated strategy of network pharmacology and AI technology.

MATERIALS AND METHODS

Bioinformatic analysis was used to analyze the expression levels, prognosis and survival of DTL and PDCD4 in cancer patients. The binding strength of OCF and DTL was simulated by molecular docking, and the affinity between them was detected by Bio-layer interferometry. Network pharmacology was used to predict the active components, potential targets and pathways of OCF. The association between key targets and their corresponding components and DTL was analyzed by Ingenuity Pathway Analysis (IPA). MTT assay, colony formation assay, wound-healing assay and transwell assay were used to verify the inhibitory effects of OCF on lung cancer cells in vitro. qRT-PCR and Western blot assay were used to detect the effects of OCF on mRNA and protein expression of DTL, PDCD4 and key genes in MAPK/JNK pathways.

RESULTS

Bioinformatics analysis showed that DTL was significantly up-regulated in lung cancer, which was associated with high malignancy rate, high metastasis rate and poor prognosis of primary tumor. PDCD4 was down-regulated in lung cancer, and associated with high metastasis rate and poor prognosis. The good affinity between OCF and DTL was predicted and verified by molecular docking and Bio-layer interferometry. Based on the network pharmacological databases, 40 active components and 220 corresponding targets of OCF were screened out. KEGG analysis showed that OCF component targets were mainly enriched in MAPK signaling pathway. IPA results showed the interrelationship between DTL, PDCD4, MAPK pathway genes and their corresponding OCF components. In addition, in vitro experiments demonstrated anti-lung cancer activity of OCF, as validated, via impairing cell viability and cell proliferation, as well as inhibiting migration and invasion abilities in lung cancer cells. qRT-PCR showed that OCF down-regulated the mRNA expression of DTL, MAP4K1, JNK, c-Jun and c-Myc, and up-regulated the mRNA expression of PDCD4 and P53 genes in A549 lung cancer cells. Western blot suggested that OCF suppressed the protein level of DTL and blocked the ubiquitination of PDCD4 in A549 lung cancer cells, and down-regulated the protein levels of MAP4K1, p-JNK and p-c-Jun while up-regulated the proteins expression level of P53.

CONCLUSIONS

OCF might elicit an anti-lung cancer effect by blocking DTL-mediated PDCD4 ubiquitination and suppression of the MAPK/JNK pathway. Meanwhile, our work revealed that network pharmacology and AI technology strategy are cogent means of studying the active components and mechanism of TCM.

Circulating cell-free messenger RNA enables non-invasive pan-tumour monitoring of melanoma therapy independent of the mutational genotype

BACKGROUND

Plasma-derived tumour-specific cell-free nucleic acids are increasingly utilized as a minimally invasive, real-time biomarker approach in many solid tumours. Circulating tumour DNA of melanoma-specific mutations is currently the best studied liquid biopsy biomarker for melanoma. However, the combination of hotspot genetic alterations covers only around 80% of all melanoma patients. Therefore, alternative approaches are needed to enable the follow-up of all genotypes, including wild-type.

METHODS

We identified KPNA2, DTL, BACE2 and DTYMK messenger RNA (mRNA) upregulated in melanoma versus nevi tissues by unsupervised data mining (N = 175 melanoma, N = 20 normal skin, N = 6 benign nevi) and experimentally confirmed differential mRNA expression in vitro (N = 18 melanoma, N = 8 benign nevi). Circulating cell-free RNA (cfRNA) was analysed in 361 plasma samples (collected before and during therapy) from 100 melanoma patients and 18 healthy donors. Absolute cfRNA copies were quantified on droplet digital PCR.

RESULTS

KPNA2, DTL, BACE2 and DTYMK cfRNA demonstrated high diagnostic accuracy between melanoma patients' and healthy donors' plasma (AUC > 86%, p < .0001). cfRNA copies increased proportionally with increasing tumour burden independently of demographic variables and even remained elevated in individuals with radiological absence of disease. Re-analysis of single-cell transcriptomes revealed a pan-tumour origin of cfRNA, including endothelial, cancer-associated fibroblasts, macrophages and B cells beyond melanoma cells as cellular sources. Low baseline cfRNA levels were associated with significantly longer progression-free survival (PFS) (KPNA2 HR = .54, p = .0362; DTL HR = .60, p = .0349) and overall survival (KPNA2 HR = .52, p = .0237; BACE2 HR = .55, p = .0419; DTYMK HR = .43, p = .0393). Lastly, we found that cfRNA copies significantly increased during therapy in non-responders compared to responders regardless of therapy and mutational subtypes and that the increase of KPNA2 (HR = 1.73, p = .0441) and DTYMK (HR = 1.82, p = .018) cfRNA during therapy was predictive of shorter PFS.

CONCLUSIONS

In sum, we identified a new panel of cfRNAs for a pan-tumour liquid biopsy approach and demonstrated its utility as a prognostic, therapy-monitoring tool independent of the melanoma mutational genotype.

LncRNA ZFPM2-AS1 drives the progression of nasopharyngeal carcinoma via modulating the downstream miR-3612/DTL signaling

LncRNA ZFPM2-AS1 has been illuminated to function as a carcinogenic driver in various human cancers. Whereas, the role of ZFPM2-AS1 in nasopharyngeal carcinoma (NPC) remains puzzled. To further understand NPC pathogenesis, we investigated the regulatory effects of ZFPM2-AS1 in NPC. Expression analysis for ZFPM2-AS1, miR-3612 and denticleless E3 ubiquitin protein ligase homolog (DTL) mRNA was carried out using real-time quantitative PCR. For the expression analysis of DTL protein, a western blot assay was applied. Cell proliferation was ascertained using the cell counting kit-8 assay and colony formation assay. Cell apoptosis was estimated based on the expression levels of BCL2-Associated X and B-cell lymphoma-2 using western blot assay. To verify the role of ZFPM2-AS1, a Xenograft model was prepared in vivo. The underlying binding between miR-3612 and ZFPM2-AS1 or DTL was validated through dual-luciferase-reporter assay or protein immunoprecipitation assay. ZFPM2-AS1 showed upregulated expression in NPC samples and cells. Meanwhile, ZFPM2-AS1 was mainly located in the cytoplasm. Knockdown of ZFPM2-AS1 restrained NPC cell proliferation and induced apoptosis, as well as suppressed tumorigenesis in animal models. ZFPM2-AS1 targeted miR-3612 whose expression was decreased in NPC samples and cells. Repression of miR-3612 aggravated NPC cell development and largely reversed the functional role of ZFPM2-AS1 silencing on NPC cell growth. MiR-3612 directly interacted with DTL, and DTL expression was upregulated in NPC. Downregulation of DTL blocked NPC cell growth, while miR-3612 inhibition partly abrogated the effects of DTL knockdown. ZFPM2-AS1 knockdown considerably restrained NPC development via targeting the miR-3612/DTL signaling. The study provided new insights to understand NPC pathogenesis.

Identification and construction of a 13-gene risk model for prognosis prediction in hepatocellular carcinoma patients

We attempted to screen out the feature genes associated with the prognosis of hepatocellular carcinoma (HCC) patients through bioinformatics methods, to generate a risk model to predict the survival rate of patients. Gene expression information of HCC was accessed from GEO database, and differentially expressed genes (DEGs) were obtained through the joint analysis of multi-chip. Functional and pathway enrichment analyses of DEGs indicated that the enrichment was mainly displayed in biological processes such as nuclear division. Based on TCGA-LIHC data set, univariate, LASSO, and multivariate Cox regression analyses were conducted on the DEGs. Then, 13 feature genes were screened for the risk model. Also, the hub genes were examined in our collected clinical samples and GEPIA database. The performance of the risk model was validated by Kaplan-Meier survival analysis and receiver operation characteristic (ROC) curves. While its universality was verified in GSE76427 and ICGC (LIRI-JP) validation cohorts. Besides, through combining patients' clinical features (age, gender, T staging, and stage) and risk scores, univariate and multivariate Cox regression analyses revealed that the risk score was an effective independent prognostic factor. Finally, a nomogram was implemented for 3-year and 5-year overall survival prediction of patients. Our findings aid precision prediction for prognosis of HCC patients.

Identification of Key Biomarkers and Pathways in Small-Cell Lung Cancer Using Biological Analysis

Background

Small-cell lung cancer (SCLC) is a major cause of carcinoma-related deaths worldwide. The aim of this study was to identify the key biomarkers and pathways in SCLC using biological analysis.

Methods

Key genes involved in the development of SCLC were identified by downloading three datasets from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened using the GEO2R online analyzer; for the functional annotation and pathway enrichment analysis of genes, Funrich software was used. Construction of protein-to-protein interaction (PPI) networks was accomplished using the Search Tool for the Retrieval of Interacting Genes (STRING), and network visualization and module identification were performed using Cytoscape.

Results

A total of 268 DEGs were ultimately obtained. The enriched functions and pathways of the upregulated DEGs included cell cycle, mitotic, and DNA replication, and the downregulated DEGs were enriched in epithelial-to-mesenchymal transition, serotonin degradation, and noradrenaline. Analysis of significant modules demonstrated that the upregulated genes are primarily concentrated in functions related to cell cycle and DNA replication. Kaplan-Meier analysis of hub genes revealed that they may promote the carcinogenesis and progression of SCLC. The result of ONCOMINE demonstrated that these 10 hub genes were significantly overexpressed in SCLC compared with normal samples.

Conclusion

Identification of the molecular functions and signaling pathways of participating DEGs can deepen the current understanding of the molecular mechanisms of SCLC. The knowledge gained from this work may contribute to the development of treatment options and improve the prognosis of SCLC in the future.

Overexpression of DTL enhances cell motility and promotes tumor metastasis in cervical adenocarcinoma by inducing RAC1-JNK-FOXO1 axis

Cervical adenocarcinoma is an important disease that affects young women and it has a high mortality and poor prognosis. Denticleless E3 ubiquitin protein ligase homolog (DTL) gene with oncogenic function has been evaluated in several cancers. Through this study, we aimed to clarify the clinical and molecular characteristics of cervical adenocarcinoma involving overexpression of DTL and elucidate its molecular mechanism. Bioinformatics analysis was performed through multiple databases. RNA sequencing was used to obtain differentially expressed genes after DTL was overexpressed in cells. The role of DTL in cervical adenocarcinoma was explored through in vitro and in vivo experiments. We found that DTL has an unfavorable prognostic implication for patients with cervical adenocarcinoma. Overexpression of DTL induced the migration and invasion of tumor cells in vitro and promoted intra-pulmonary metastasis in vivo. In addition, DTL activated JNK through RAC1 and upregulated FOXO1 to induce epithelial-mesenchymal transition, and the migration and invasion of tumor cells. Therefore, we conclude that overexpression of DTL enhanced cell motility and promoted tumor metastasis of cervical adenocarcinoma by regulating the RAC1-JNK-FOXO1 axis. These results suggest that DTL may become a potential therapeutic target for antitumor metastasis of cervical adenocarcinoma.

MiR-490-5p Restrains Progression of Gastric cancer through DTL Repression

Gastric cancer (GC) accounts for a main cause of cancer-related deaths. This study sought for molecular mechanism of miR-490-5p/DTL axis in affecting GC progression, thus bringing new hope for treatment of GC. Expression data of differentially expressed miRNAs and mRNAs in GC tissue from TCGA database were analyzed. MiR-490-5p and DTL mRNA expression levels in GC were evaluated with qRT-PCR. Cell viability was confirmed with CCK-8 method. Cell cycle distribution and apoptosis were analyzed with flow cytometry. Cell migratory and invasive potential was proved with Transwell assay. The targeted relationship between DTL and miR-490-5p was analyzed with dual-luciferase assay. The results indicated a decreased miR-490-5p level in GC cells. MiR-490-5p upregulation hampered proliferation, migration, invasion and promote cell apoptosis. DTL was the target of and inversely associated with miR-490-5p, and it could remarkably induce the carcinogenesis of GC. MiR-490-5p mediated GC cell progression by DTL repression. In conclusion, miR-490-5p and DTL may be valuable in diagnosis and treatment for GC.

Identification of genes associated with clinicopathological features of colorectal cancer

Objective

To identify genes associated with the clinicopathological features of colorectal cancer (CRC).

Methods

Gene expression profiles were downloaded and preprocessed by GEOquery and affy R packages, respectively. The limma package was applied to identify the differentially expressed genes (DEGs) in CRC. Gene Ontology and Kyoto Gene and Genome Encyclopedia (KEGG) pathway enrichment analyses for the DEGs were carried out using the clusterProfiler package. Protein–protein interaction (PPI) and weighted gene co-expression (WGC) networks were constructed using the STRING database and WGCNA package, respectively.

Results

A total of 523 DEGs (283 downregulated and 240 upregulated genes) in CRC tissues were identified. These DEGs were mainly enriched in 111 biological processes, 16 cellular components and 40 molecular functions, such as proteinaceous extracellular matrix, extracellular structure organization and chemokine-mediated signalling pathway. PPI and WGC networks showed that four upregulated genes (KIF2C, CDC45, CEP55 and DTL) were key genes. Subgroup analysis based on individual cancer stages and histological subtypes indicated that the expression of these key genes was upregulated in CRC stages I–IV, adenocarcinoma and mucinous adenocarcinoma.

Conclusions

The study provides new insights into understanding the pathogenesis of CRC. These identified genes may act as potential targets for CRC diagnosis and treatment.

Bioinformatics analysis of lncRNA‑associated ceRNA network in melanoma

Melanoma is an extremely malignant tumor with early metastasis and high mortality. Little is known about the process of by which melanoma occurs, as its mechanism is very complex and only limited data are available on its long non-coding RNA (lncRNA)-associated competing endogenous RNAs (ceRNAs). The purpose of this study was to screen out potential prognostic molecules and identify a ceRNA network related to the occurrence of melanoma. We screened 169 differentially expressed mRNAs (DEmRNAs) from E-MTAB-1862 and GSE3189; gene ontology (GO) enrichment analysis showed that these genes were closely related to the development of skin. In the protein-protein interaction network, we screened out a total of 19 hub genes. Furthermore, we predicted the microRNAs (miRNAs) that regulate hub genes using the miRWalk database and then intersected these with GSE35579, resulting in nine DEmiRNAs. We also predicted the lncRNAs that regulate the miRNAs using the LncBasev.2 database. According to the ceRNA hypothesis, and based on the intersection of the DElncRNAs with merged GTEx and TCGA data, we obtained 20 DElncRNAs. A total of four DEmRNAs, nine DEmiRNAs, and 20 DElncRNAs were included in the ceRNA network. Based on Cox stepwise regression and survival analysis, we identified five biomarkers, ZSCAN16-AS1, LINC00520, XIST, DTL, and let-7a-5p, and obtained risk scores. The results showed that most of the differentially expressed genes were related to epithelial-mesenchymal transition (EMT) in melanoma. Finally, we obtained a LINC00520/let-7a-5p/DTL molecular regulatory network. These results suggest that ceRNA networks have an important role in evaluating the prognosis of patients with melanoma and provide a new experimental basis for exploring the EMT process in the development of melanoma.

KIF14 and KIF23 Promote Cell Proliferation and Chemoresistance in HCC Cells, and Predict Worse Prognosis of Patients with HCC

Background

Hepatocellular carcinoma (HCC) is one of the most common human malignant tumors. The prognosis of HCC patients is still unsatisfying. In this study, we performed the integrated bioinformatics analysis to identify potential biomarkers and biological pathways in HCC.

Methods

Gene expression profiles were obtained from the Gene Expression Omnibus database (GSE55048, GSE55758, and GSE56545) for the screening of the common differentially expressed genes (DEGs) between HCC tissues and matched non-tumor tissues. DEGs were subjected to Gene Ontology, KEGG pathway, and Reactome pathway analysis. The hub genes were identified by using protein–protein interaction (PPI) network analysis. The hub genes in HCC were further subjected to overall survival analysis of HCC patients. The hub genes were further validated by in vitro functional assays.

Results

A total of 544 common differentially expressed genes were screened from three datasets. Gene Ontology, KEGG and Reactome analysis results showed that DEGs are significantly associated with the biological process of cell cycle, cell division, and DNA replication. PPI network analysis identified 20 hub genes from the DEGs. These hub genes except CENPE were all significantly up-regulated in the HCC tissues when compared to non-tumor tissues. The Kaplan–Meier survival analysis results showed that the high expression of the 20 hub genes was associated with shorter survival of the HCC patients. Further validation studies showed that knockdown of KIF14 and KIF23 both suppressed the proliferative potential, increased the caspase-3/-7 activity, up-regulated Bax expression, and promoted the invasive and migratory abilities in the HCC cells. In addition, knockdown of KIF14 and KIF23 enhanced chemosensitivity to cisplatin and sorafenib in the HCC cells. Finally, the high expression of KIF14 and KIF23 was associated with shorter progression-free survival, recurrence-free survival, and disease-specific survival of patients with HCC.

Conclusion

In conclusion, the present study performed the integrated bioinformatics analysis and showed that KIF14 and KIF23 silence attenuated cell proliferation, invasion, and migration, and promoted chemosensitivity of HCC cells. KIF14 and KIF23 may serve as potential biomarkers for predicting the worse prognosis of patients with HCC.

MCM2 and NUSAP1 Are Potential Biomarkers for the Diagnosis and Prognosis of Pancreatic Cancer

Pancreatic cancer (PC) is one of the most malignant tumors. Despite considerable progress in the treatment of PC, the prognosis of patients with PC is poor. The aim of this study was to identify potential biomarkers for the diagnosis and prognosis of PC. First, the original data of three independent mRNA expression datasets were downloaded from the Gene Expression Omnibus and The Cancer Genome Atlas databases and screened for differentially expressed genes (DEGs) using the R software. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of the DEGs were performed, and a protein-protein interaction (PPI) network was constructed to screen for hub genes. The hub genes were analyzed for genetic variations, as well as for survival, prognostic, and diagnostic value, using the cBioPortal and Gene Expression Profiling Interactive Analysis (GEPIA) databases and the pROC package. After screening for potential biomarkers, the mRNA and protein levels of the biomarkers were verified at the tissue and cellular levels using the Cancer Cell Line Encyclopedia, GEPIA, and the Human Protein Atlas. As a result, a total of 248 DEGs were identified. The GO terms enriched in DEGs were related to the separation of mitotic sister chromatids and the binding of the spindle to the extracellular matrix. The enriched pathways were associated with focal adhesion, ECM-receptor interaction, and phosphatidylinositol 3-kinase (PI3K)/AKT signaling. The top 20 genes were selected from the PPI network as hub genes, and based on the analysis of multiple databases, MCM2 and NUSAP1 were identified as potential biomarkers for the diagnosis and prognosis of PC. In conclusion, our results show that MCM2 and NUSAP1 can be used as potential biomarkers for the diagnosis and prognosis of PC. The study also provides new insights into the underlying molecular mechanisms of PC.

Transcriptome analyses identify hub genes and potential mechanisms in adenoid cystic carcinoma

Adenoid cystic carcinoma (ACC) is one of the most frequent malignancies of salivary glands. The objective of this study was to identify key genes and potential mechanisms during ACC samples.The gene expression profiles of GSE88804 data set were downloaded from Gene Expression Omnibus. The GSE88804 data set contained 22 samples, including 15 ACC samples and 7 normal salivary gland tissues. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were constructed, and protein-protein interaction network of differentially expressed genes (DEGs) was performed by Cytoscape. The top 10 hub genes were analyzed based on Gene Expression Profiling Interactive Analysis. Then, DEGs between ACC samples and normal salivary gland samples were analyzed by gene set enrichment analysis. Furthermore, miRTarBase and Cytoscape were used for visualization of miRNA-mRNA regulatory network. KEGG pathway analysis was undertaken using DIANA-miRPath v3.0.In total, 382 DEGs were identified, including 119 upregulated genes and 263 downregulated genes. GO analysis showed that DEGs were mainly enriched in extracellular matrix organization, extracellular matrix, and calcium ion binding. KEGG pathway analysis showed that DEGs were mainly enriched in p53 signaling pathway and salivary secretion. Expression analysis and survival analysis showed that ANLN, CCNB2, CDK1, CENPF, DTL, KIF11, and TOP2A are all highly expressed, which all may be related to poor overall survival. Predicted miRNAs of 7 hub DEGs mainly enriched in proteoglycans in cancer and pathways in cancer.This study indicated that identified DEGs and hub genes might promote our understanding of molecular mechanisms, which might be used as molecular targets or diagnostic biomarkers for ACC.

Highly efficient polyethylene glycol-functionalised gold nanorods for photothermal ablation of hepatocellular carcinoma cells

Gold nanorods (GNRs) with exceptional photothermal properties have held promising potential for application in the biomedical field. In this study, the authors achieved photothermal ablation by polyethylene glycol (PEG)-functionalised GNRs. Well-dispersed and uniform GNRs were produced through a seed-mediated growth method. A thermal camera was used to scrutinise the temperature distribution and efficiency of the photothermal properties of the GNRs, which were irradiated by an 808 nm laser on a silicon chip. They observed that the GNRs provided about a 5°C temperature increase and produced hyperthermia efficiently. Since GNRs need to be surface tailored with a biocompatible material rather than cetyltrimethylammonium bromide (CTAB), they chose methoxyl PEG thiol to modify the GNRs. By taking advantage of the alkaline environment that assists this functionalisation, they accomplished about 89% removal of CTAB and identified a PEG layer on the surface of the GNRs. The GNR biocompatibility was considerably improved without any shift of the optical properties. Hepatocellular carcinoma cells were incubated with GNRs for 24 h and then were irradiated with a near-infrared laser for 3 min. Few cells remained alive, which demonstrated the photothermal ablation ability of the GNRs.

Identification of Flap endonuclease 1 as a potential core gene in hepatocellular carcinoma by integrated bioinformatics analysis

Hepatocellular carcinoma (HCC) is a common yet deadly form of malignant cancer. However, the specific mechanisms involved in HCC diagnosis have not yet fully elucidated. Herein, we screened four publically available Gene Expression Omnibus (GEO) expression profiles (GSE14520, GSE29721, GSE45267 and GSE60502), and used them to identify 409 differentially expressed genes (DEGs), including 142 and 267 up- and down-regulated genes, respectively. The DAVID database was used to look for functionally enriched pathways among DEGs, and the STRING database and Cytoscape platform were used to generate a protein-protein interaction (PPI) network for these DEGs. The cytoHubba plug-in was utilized to detect 185 hub genes, and three key clustering modules were constructed with the MCODE plug-in. Gene functional enrichment analyses of these three key clustering modules were further performed, and nine core genes including BIRC5, DLGAP5, DTL, FEN1, KIAA0101, KIF4A, MCM2, MKI67, and RFC4, were identified in the most critical cluster. Subsequently, the hierarchical clustering and expression of core genes in TCGA liver cancer tissues were analyzed using the UCSC Cancer Genomics Browser, and whether elevated core gene expression was linked to a poor prognosis in HCC patients was assessed using the GEPIA database. The PPI of the nine core genes revealed an interaction between FEN1, MCM2, RFC4, and BIRC5. Furthermore, the expression of FEN1 was positively correlated with that of three other core genes in TCGA liver cancer tissues. FEN1 expression in HCC and other tumor types was assessed with the FIREBROWSE and ONCOMINE databases, and results were verified in HCC samples and hepatoma cells. FEN1 levels were also positively correlated with tumor size, distant metastasis and vascular invasion. In conclusion, we identified nine core genes associated with HCC development, offering novel insight into HCC progression. In particular, the aberrantly elevated FEN1 may represent a potential biomarker for HCC diagnosis and treatment.

Bioinformatic validation identifies candidate key genes in diffuse large-B cell lymphoma

Aim: In this study, four datasets concerning 167 diffuse large B-cell lymphoma (DLBCL) patients versus 56 controls and seven datasets involving 280 germinal center B-cell like (GCB) versus 224 activated B-cell like (ABC) DLBCL were included. Materials & methods: We identified 80 different expression genes (DEGs) for DLBCL versus nontumor and 77 DEGs for GCB versus ABC DLBCL. Results: These DEGs were found to be enriched in cell activity, signal transduction and extracellular region. Then ten central node genes for DLBCL versus nontumor and two hub genes for GCB versus ABC DLBCL were identified. Last, PAICS, IRF4 and PTPN1 were explored to be correlated with poor prognosis in DLBCL patients. Conclusion: Our study has identified critical genes from transcriptional profiles for DLBCL.