Identification and analysis of circRNA–miRNA–mRNA regulatory network in hepatocellular carcinoma

This study was to identify important circRNA–miRNA–mRNA (ceRNAs) regulatory mechanisms in hepatocellular carcinoma (HCC). The circRNA dataset {"type":"entrez-geo","attrs":{"text":"GSE97332","term_id":"97332"}}GSE97332 and miRNA dataset {"type":"entrez-geo","attrs":{"text":"GSE57555","term_id":"57555"}}GSE57555 were used for analyses. Functional enrichment analysis for miRNA and target gene was conducted using cluster Profiler. Survival analysis was conducted through R package Survival. The ceRNAs and drug–gene interaction networks were constructed. The ceRNAs network contained five miRNAs including hsa‐miR‐25‐3p, hsa‐miR‐3692‐5p, hsa‐miR‐4270, hsa‐miR‐331‐3p, and hsa‐miR‐125a‐3p. Among the network, hsa‐miR‐25‐3p targeted the most genes, hsa‐miR‐3692‐5p and hsa‐miR‐4270 were targeted by more circRNAs than other miRNAs, hsa‐circ‐0034326 and hsa‐circ‐0011950 interacted with three miRNAs. Furthermore, target genes, including NRAS, ITGA5, SLC7A1, SEC14L2, SLC12A5, and SMAD2 were obtained in drug–gene interaction network. Survival analysis showed NRAS, ITGA5, SLC7A1, SEC14L2, SLC12A5, and SMAD2 were significantly associated with prognosis of HCC. NRAS, ITGA5, and SMAD2 were significantly enriched in proteoglycans in cancer. Moreover, hsa‐circ‐0034326 and hsa‐circ‐0011950 might function as ceRNAs to play key roles in HCC. Furthermore, miR‐25‐3p, miR‐3692‐5p, and miR‐4270 might be significant for HCC development. NRAS, ITGA5, SEC14L2, SLC12A5, and SMAD2 might be prognostic factors for HCC patients via proteoglycans in cancer pathway. Taken together, the findings will provide novel insight into pathogenesis, selection of therapeutic targets and prognostic factors for HCC.Inspec keywords: cancer, cellular biophysics, patient diagnosis, bioinformatics, tumours, biochemistry, molecular biophysics, genetics, drugs, RNAOther keywords: ITGA5, SMAD2, hsa‐circ‐0034326, SEC14L2, SLC12A5, target gene, survival analysis, drug–gene interaction network, miRNAs, hsa‐miR‐25‐3p, hsa‐miR‐3692‐5p, hsa‐miR‐4270, hsa‐miR‐331‐3p, hsa‐miR‐125a‐3p, hsa‐circ‐0011950, SLC7A1, pathogenesis, therapeutic targets, prognostic factors, circRNA‐miRNA‐mRNA regulatory network, current 125.0 A     

Functional role of microRNA‐500a‐3P‐loaded liposomes in the treatment of cisplatin‐induced AKI

Cisplatin treatment results in acute kidney injury (AKI) by the phosphorylation of mixed lineage kinase domain‐like protein (MLKL). The knockout of MLKL, which is a principle mediator of necroptosis, is believed to alleviate the AKI symptoms. The present study was aimed to improve the therapeutic efficacy in AKI. For this purpose, miR‐500a‐3P was identified as appropriate miRNA therapeutics and loaded in liposome delivery carrier. The authors have showed that the miR‐LIP directly controls the expression of RIPK3 and MLKL – a modulator of necroptosis and thereby reduces the severity of kidney injury. The miR‐LIP significantly controlled the phosphorylation of MLKL compared to that of CDDP‐treated HK2 cells. Similar results are observed with RIPK3. The miR‐LIP has also been demonstrated to control the inflammatory response in tubular cells. Western blot analysis further revealed that the phosphorylation of P‐65 was mainly responsible for the inflammatory response and miR‐LIP significantly decreased the CDDP‐induced NF‐kB phosphorylation. Overall, the present study explored the molecular mechanism behind the necroptosis in AKI and potential of miRNA in targeting MLKL pathways. Study further highlights the potential advantage of liposome as a delivery carrier for miRNA therapeutics.Inspec keywords: medical disorders, biochemistry, cancer, cellular biophysics, kidney, enzymes, drugs, toxicology, patient treatment, injuries, genetics, molecular biophysicsOther keywords: current 500.0 A, functional role, microRNA‐500a‐3P‐loaded liposomes, cisplatin‐induced AKI, cisplatin treatment results, acute kidney injury, phosphorylation, mixed lineage kinase domain, necroptosis, AKI symptoms, therapeutic efficacy, appropriate miRNA therapeutics, liposome delivery carrier, miR‐LIP, RIPK3, inflammatory response, CDDP‐induced NF‐kB, MLKL pathways     

Micro RNA‐30b (inhibitor) nanoparticles suppressed the lipopolysaccharide (LPS)‐induced acute kidney injury

The main aim of present study is to evaluate the effect of miR‐30b on the function of human proximal tubular epithelial cell line HK‐2 cells. For this purpose, miRNA was loaded in an ionically cross‐linked polysaccharide nanoparticle. The authors have demonstrated the influence of miR‐30b mimic and inhibitor in HK‐2 cell killing effect. Lipopolysaccharide (LPS) significantly increased the level of inflammatory cytokines of TNF‐α, IL‐1β and level was further increased with the treatment of PAg‐miR mimic consistent with the cell viability assay. Interestingly, PAg‐miR inhibitor significantly downregulated the expression of inflammatory cytokines and thereby reduced the inflammation in the body. Western blot analysis showed that LPS induced severe apoptosis of HK‐2 cells and the apoptosis was further promoted by the PAg‐miR (mimic). In contrast, PAg‐miR (inhibitor) alleviated the apoptosis of HK‐2 cells as indicated in the significantly reduced levels of Bax and c‐Caspase‐3 proteins. Overall, miR‐30b promoted LPS‐induced HK‐2 cell inflammatory injury by inducing the apoptosis and by releasing inflammatory cytokines, as well as by impairing autophagy process.Inspec keywords: biomedical materials, nanoparticles, molecular biophysics, enzymes, toxicology, injuries, nanomedicine, RNA, cellular biophysics, kidney, proteins, drugs, biochemistryOther keywords: microRNA‐30b, nanoparticles suppressed the lipopolysaccharide (LPS)‐induced, main aim, human proximal tubular epithelial cell line HK‐2 cells, polysaccharide nanoparticle, HK‐2 cell killing effect, inflammatory cytokines, IL‐1β, cell viability assay, PAg‐miR inhibitor, apoptosis, reduced levels, LPS‐induced HK‐2 cell inflammatory injury     

Identification of self‐regulatory network motifs in reverse engineering gene regulatory networks using microarray gene expression data

Gene Regulatory Networks (GRNs) are reconstructed from the microarray gene expression data through diversified computational approaches. This process ensues in symmetric and diagonal interaction of gene pairs that cannot be modelled as direct activation, inhibition, and self‐regulatory interactions. The values of gene co‐expressions could help in identifying co‐regulations among them. The proposed approach aims at computing the differences in variances of co‐expressed genes rather than computing differences in values of mean expressions across experimental conditions. It adopts multivariate co‐variances using principal component analysis (PCA) to predict an asymmetric and non‐diagonal gene interaction matrix, to select only those gene pair interactions that exhibit the maximum variances in gene regulatory expressions. The asymmetric gene regulatory interactions help in identifying the controlling regulatory agents, thus lowering the false positive rate by minimizing the connections between previously unlinked network components. The experimental results on real as well as in silico datasets including time‐series RTX therapy, Arabidopsis thaliana, DREAM‐3, and DREAM‐8 datasets, in comparison with existing state‐of‐the‐art approaches demonstrated the enhanced performance of the proposed approach for predicting positive and negative feedback loops and self‐regulatory interactions. The generated GRNs hold the potential in determining the real nature of gene pair regulatory interactions.Inspec keywords: molecular biophysics, principal component analysis, genetics, biology computing, reverse engineeringOther keywords: controlling regulatory agents, interacting genes, unlinked network components, self‐regulatory interactions, gene pair regulatory interactions, self‐regulatory network motifs, reverse engineering gene regulatory networks, microarray gene expression data, diversified computational approaches, symmetric interaction, diagonal interaction, gene pairs, gene co‐expressions, co‐expressed genes, mean expressions, gene regulatory expressions, asymmetric gene regulatory interactions     

Induction of extrinsic and intrinsic apoptosis in cervical cancer cells by Momordica dioica mediated gold nanoparticles

Bio‐fabrication of gold nanoparticles (AuNPs) has several advantages like biocompatibility, less toxicity, and eco‐friendly in nature over their chemical and physical methods. Currently, the authors fabricated AuNPs using aqueous root extract of Momordica dioica (M. dioica) and explored their anticancer application with mechanistic approaches. Different biophysical techniques such as UV–visible spectroscopy, Fourier transform infrared, X‐ray diffraction, transmission electron microscopy, selected area electron diffraction, and dynamic light scattering were employed for AuNPs characterisation. The synthesised AuNPs were mono‐dispersed, crystalline in nature, anionic surface (−23.9 mV), and spherical particle of an average diameter of 9.4 nm. In addition, the AuNPs were stable in buffers solutions and also biocompatible towards normal human cells (human vascular endothelial cells and human lung cells). The AuNPs were exhibited anticancer activity against different cancer cell lines such as human breast cancer cells, human cervical cancer cells (HeLa) and human lung cancer cells. Further, the pro‐apoptotic genes such as Bcl₂ were down‐regulated and BAX, Caspase‐3, −8, and −9 were up‐regulated in HeLa cells as compared to untreated cells. Annexin‐V‐FITC assay results showed that the AuNPs were induced apoptosis by accumulation of intracellular reactive oxygen species. To their knowledge, this is the first report on the synthesis of bioactive metal nanoparticles from M. dioica and it may open up new avenues in therapeutic applications.Inspec keywords: nanomedicine, tumours, lung, visible spectra, drug delivery systems, cancer, transmission electron microscopy, biomedical materials, molecular biophysics, light scattering, toxicology, electron diffraction, X‐ray diffraction, ultraviolet spectra, biomembranes, drugs, gold, biochemistry, particle size, cellular biophysics, nanoparticles, nanofabrication, Fourier transform infrared spectraOther keywords: extrinsic apoptosis, intrinsic apoptosis, mediated gold nanoparticles, biofabrication, physical methods, biophysical techniques, UV‐visible spectroscopy, X‐ray diffraction, transmission electron microscopy, selected area electron diffraction, AuNPs characterisation, normal human cells, human vascular endothelial cells, cancer cell lines, human breast cancer cells, human cervical cancer cells, human lung cancer cells, HeLa cells, untreated cells, bioactive metal nanoparticles, Momordica dioica mediated gold nanoparticles, Fourier transform infrared spectra, proapoptotic genes, Bcl₂ , BAX, Caspase‐3, Caspase‐9, Caspase‐8, Annexin‐V‐FITC assay, intracellular reactive oxygen species, therapeutic applications, voltage ‐23.9 mV, size 9.4 nm, Au     

Discovery of significant pathways in breast cancer metastasis via module extraction and comparison

Discovering significant pathways rather than single genes or small gene sets involved in metastasis is becoming more and more important in the study of breast cancer. Many researches have shed light on this problem. However, most of the existing works are relying on some priori biological information, which may bring bias to the models. The authors propose a new method that detects metastasis‐related pathways by identifying and comparing modules in metastasis and non‐metastasis gene co‐expression networks. The gene co‐expression networks are built by Pearson correlation coefficients, and then the modules inferred in these two networks are compared. In metastasis and non‐metastasis networks, 36 and 41 significant modules are identified. Also, 27.8% (metastasis) and 29.3% (non‐metastasis) of the modules are enriched significantly for one or several pathways with p ‐value <0.05. Many breast cancer genes including RB1, CCND1 and TP53 are included in these identified pathways. Five significant pathways are discovered only in metastasis network: glycolysis pathway, cell adhesion molecules, focal adhesion, stathmin and breast cancer resistance to antimicrotubule agents, and cytosolic DNA‐sensing pathway. The first three pathways have been proved to be closely associated with metastasis. The rest two can be taken as a guide for future research in breast cancer metastasis.Inspec keywords: cancer, genetics, genomics, DNA, molecular biophysics, adhesion, cellular biophysicsOther keywords: breast cancer metastasis, module extraction, gene sets, metastasis‐related pathways, nonmetastasis gene coexpression networks, Pearson correlation coefflcients, breast cancer genes, RB1, CCND1, TP53, glycolysis pathway, cell adhesion molecules, focal adhesion, stathmin, breast cancer resistance, antimicrotubule agents, cytosolic DNA‐sensing pathway, breast cancer metastasis     

Antibacterial and anticancer activity of biosynthesised CuO nanoparticles

The present investigation aims for the synthesis of copper oxide nanoparticles (CuO NPs) using Nilgirianthus ciliatus plant extract. The obtained CuO NPs were characterised by X‐ray diffraction, Fourier transform infrared spectrum, ultraviolet–visible spectroscopy, photoluminescence, scanning electron microscopy and transmission electron microscopy analysis. Significant bacterial activity was manifested by CuO nanoparticles against both Gram‐positive (Staphylococcus aureus and Staphylococcus mutans) and Gram‐negative (Escherichia coli and Pseudomonas aeruginosa) bacteria. The synthesised CuO NPs have good cytotoxicity against both human breast cancer cell line (MCF‐7) and lung cancer cell line (A549) with minimum cytotoxic effect on normal L929 (fibroblast) cell lines.Inspec keywords: microorganisms, ultraviolet spectra, nanomedicine, transmission electron microscopy, visible spectra, cellular biophysics, antibacterial activity, nanoparticles, X‐ray diffraction, lung, copper compounds, cancer, toxicology, biomedical materials, scanning electron microscopy, photoluminescence, Fourier transform infrared spectraOther keywords: antibacterial activity, anticancer activity, biosynthesised CuO nanoparticles, copper oxide nanoparticles, Nilgirianthus ciliatus plant, X‐ray diffraction, infrared spectrum, ultraviolet–visible spectroscopy, transmission electron microscopy analysis, bacterial activity, Gram‐negative bacteria, synthesised CuO NPs, human breast cancer cell line, Staphylococcus aureus, Staphylococcus mutans, CuO     

MicroRNAs and their target mRNAs as potential biomarkers among smokers and non‐smokers with lung adenocarcinoma

Lung adenocarcinoma is one of the major causes of mortality. Current methods of diagnosis can be improved through identification of disease specific biomarkers. MicroRNAs are small non‐coding regulators of gene expression, which can be potential biomarkers in various diseases. Thus, the main objective of this study was to gain mechanistic insights into genetic abnormalities occurring in lung adenocarcinoma by implementing an integrative analysis of miRNAs and mRNAs expression profiles in the case of both smokers and non‐smokers. Differential expression was analysed by comparing publicly available lung adenocarcinoma samples with controls. Furthermore, weighted gene co‐expression network analysis is performed which revealed mRNAs and miRNAs significantly correlated with lung adenocarcinoma. Moreover, an integrative analysis resulted in identification of several miRNA–mRNA pairs which were significantly dysregulated in non‐smokers with lung adenocarcinoma. Also two pairs (miR‐133b/Protein Kinase C Zeta (PRKCZ) and miR‐557/STEAP3) were found specifically dysregulated in smokers. Pathway analysis further revealed their role in important signalling pathways including cell cycle. This analysis has not only increased the authors’ understanding about lung adenocarcinoma but also proposed potential biomarkers. However, further wet laboratory studies are required for the validation of these potential biomarkers which can be used to diagnose lung adenocarcinoma.Inspec keywords: cancer, molecular biophysics, patient diagnosis, tumours, RNA, proteins, lung, genetics, medical diagnostic computing, molecular configurationsOther keywords: miRNAs expression profiles, mRNAs expression profiles, smokers, nonsmokers, integrative analysis, lung adenocarcinoma, microRNAs, disease specific biomarkers, noncoding regulators, genetic abnormalities, weighted gene coexpression network analysis     

Cancer adjuvant chemotherapy prediction model for non‐small cell lung cancer

Non‐small cell lung cancer (NSCLC) is the most popular and dangerous type of lung cancer. Adjuvant chemotherapy (ACT) is the main treatment after surgery resection to prevent the patient from cancer recurrence. However, ACT could be toxic and unhelpful in some cases. Therefore, it is highly desired in clinical applications to predict the treatment outcomes of chemotherapy. Conventional methods of predicting cancer treatment rely solely on histopathology and the results are not reliable in some cases. This study aims at building a predictive model to identify who needs ACT treatment and who should avoid it. To this end, the authors propose an innovative method to identify NSCLC‐related prognostic genes from microarray gene‐expression datasets. They also propose a new model using gene‐expression programming algorithm for ACT classification. The proposed model was evaluated on integrated microarray datasets from four institutes and compared with four representative methods: general regression neural network, decision tree, support vector machine and naive Bayes. Evaluation results demonstrated the effectiveness of the proposed model with accuracy 89.8% which is higher than other representative models. They obtained four probes (four genes) that can get good prediction results. These genes are 204891_s_at (LCK), 208893_s_at (DUSP6), 202454_s_at (ERBB3) and 201076_at (MMD).Inspec keywords: neural nets, regression analysis, decision trees, surgery, medical computing, cancer, cellular biophysics, lung, genetics, support vector machines, Bayes methods, biochemistryOther keywords: cancer ACT prediction model, nonsmall cell lung cancer, adjuvant chemotherapy, surgery resection, cancer recurrence, conventional methods, cancer treatment, microarray gene‐expression technology, NSCLC treatment, ACT treatment, NSCLC‐related prognostic genes, microarray gene‐expression datasets, gene‐expression programming algorithm, ACT classification, ACT information, integrated microarray datasets, representative models, survival time, general regression neural network, decision tree, support vector machine, naive Bayes     

Fold change based approach for identification of significant network markers in breast,lung and prostate cancer

Cancer belongs to a class of highly aggressive diseases and a leading cause of death in the world. With more than 100 types of cancers, breast, lung and prostate cancer remain to be the most common types. To identify essential network markers (NMs) and therapeutic targets in these cancers, the authors present a novel approach which uses gene expression data from microarray and RNA‐seq platforms and utilises the results from this data to evaluate protein–protein interaction (PPI) network. Differentially expressed genes (DEGs) are extracted from microarray data using three different statistical methods in R, to produce a consistent set of genes. Also, DEGs are extracted from RNA‐seq data for the same three cancer types. DEG sets found to be common in both platforms are obtained at three fold change (FC) cut‐off levels to accurately identify the level of change in expression of these genes in all three cancers. A cancer network is built using PPI data characterising gene sets at log‐FC (LFC)>1, LFC>1.5 and LFC>2, and interconnection between principal hub nodes of these networks is observed. Resulting network of hubs at three FC levels highlights prime NMs with high confidence in multiple cancers as validated by Gene Ontology functional enrichment and maximal complete subgraphs from CFinder.Inspec keywords: cancer, proteins, RNA, bioinformatics, statistical analysis, genetics, molecular biophysics, ontologies (artificial intelligence), lungOther keywords: cancer network, PPI data, gene sets, multiple cancers, Gene Ontology functional enrichment, prostate cancer, gene expression data, RNA‐seq platforms, protein–protein interaction network, DEG, microarray data, RNA‐seq data, cancer types, lung cancer, diseases, breast cancer, network markers, differentially expressed genes, fold change based approach, CFinder, statistical methods     

Bifurcation analysis of insulin regulated mTOR signalling pathway in cancer cells

Insulin induced mTOR signalling pathway is a complex network implicated in many types of cancers. The molecular mechanism of this pathway is highly complex and the dynamics is tightly regulated by intricate positive and negative feedback loops. In breast cancer cell lines, metformin has been shown to induce phosphorylation at specific serine sites in insulin regulated substrate of mTOR pathway that results in apoptosis over cell proliferation. The author models and performs bifurcation analysis to simulate cell proliferation and apoptosis in mTOR signalling pathway to capture the dynamics both in the presence and absence of metformin in cancer cells. Metformin is shown to negatively regulate PI3K through AMPK induced IRS1 phosphorylation and this brings about a reversal of AKT bistablity in codimension‐1 bifurcation diagram from S‐shaped, related to cell proliferation in the absence of drug metformin, to Z‐shaped, related to apoptosis in the presence of drug metformin. The author hypothesises and explains how this negative regulation acts a circuit breaker, as a result of which mTOR network favours apoptosis of cancer cells over its proliferation. The implication of reversing the shape of bistable dynamics from S to Z or vice‐versa in biological networks in general is discussed.Inspec keywords: bifurcation, molecular biophysics, drugs, enzymes, biochemistry, cellular biophysics, cancer, biomedical materialsOther keywords: intricate positive feedback loops, negative feedback loops, breast cancer cell lines, insulin regulated substrate, cell proliferation, cancer cells, AMPK induced IRS1 phosphorylation, codimension‐1 bifurcation diagram, drug metformin, mTOR network, insulin regulated mTOR signalling pathway, bifurcation analysis, PI3K, AKT bistablity     

Classification of drug molecules for oxidative stress signalling pathway

In humans, oxidative stress is involved in the development of diabetes, cancer, hypertension, Alzheimers’ disease, and heart failure. One of the mechanisms in the cellular defence against oxidative stress is the activation of the Nrf2‐antioxidant response element (ARE) signalling pathway. Computation of activity, efficacy, and potency score of ARE signalling pathway and to propose a multi‐level prediction scheme for the same is the main aim of the study as it contributes in a big amount to the improvement of oxidative stress in humans. Applying the process of knowledge discovery from data, required knowledge is gathered and then machine learning techniques are applied to propose a multi‐level scheme. The validation of the proposed scheme is done using the K‐fold cross‐validation method and an accuracy of 90% is achieved for prediction of activity score for ARE molecules which determine their power to refine oxidative stress.Inspec keywords: cancer, cellular biophysics, biochemistry, drugs, molecular biophysics, proteins, learning (artificial intelligence), medical computingOther keywords: oxidative stress, Nrf2‐antioxidant response element signalling pathway, ARE signalling pathway, diabetes, cancer, hypertension, Alzheimers’ disease, heart failure, machine learning techniques, K‐fold cross‐validation method, ARE molecules     

Facile synthesis of multi‐walled carbon nanotube via folic acid grafted nanoparticle for precise delivery of doxorubicin

The motive of work was to develop a multi‐walled carbon nanoplatform through facile method for transportation of potential anticancer drug doxorubicin (DOX). Folic acid (FA)‐ethylene diamine (EDA) anchored and acid functionalised MWCNTs were covalently grafted with DOX via π–π stacking interaction. The resultant composite was corroborated by ¹ H NMR, FTIR, XRD, EDX, SEM, and DSC study. The drug entrapment efficiency of FA‐conjugated MWCNT was found high and stability study revealed its suitability in biological system. FA‐EDA‐MWCNTs‐DOX conjugate demonstrated a significant in vitro anticancer activity on human breast cancer MCF‐7 cells. MTT study revealed the lesser cytotoxicity of folate‐conjugated MWCNTs. The obtained results demonstrated the targeting specificity of FA‐conjugate via overexpressed folate receptor deemed greater scientific value to overcome multidrug protection during cancer therapy. The proposed strategy is a gentle contribution towards development of biocompatible targeted drug delivery and offers potential to address the current challenges in cancer therapy.Inspec keywords: toxicology, nanoparticles, biomedical materials, scanning electron microscopy, drug delivery systems, nanofabrication, nanomedicine, nanocomposites, cellular biophysics, cancer, drugs, multi‐wall carbon nanotubes, Fourier transform infrared spectra, X‐ray chemical analysis, differential scanning calorimetry, proton magnetic resonance, organic compoundsOther keywords: facile synthesis, multiwalled carbon nanotube, precise delivery, multiwalled carbon nanoplatform, drug entrapment efficiency, FA‐conjugated MWCNT, stability study, biological system, human breast cancer MCF‐7 cells, MTT study, folate‐conjugated MWCNTs, overexpressed folate receptor, cancer therapy, biocompatible targeted drug delivery, anticancer drug doxorubicin, π‐π stacking interaction, composite material, ¹ H NMR, in vitro anticancer activity, folic acid grafted nanoparticle, folic acid‐ethylene diamine, acid functionalised MWCNT, FTIR spectra, XRD, EDX, SEM, FA‐EDA‐MWCNT‐DOX conjugate, cytotoxicity, DSC, C     

Trastuzumab‐conjugated nanoparticles composed of poly(butylene adipate‐co ‐butylene terephthalate) prepared by electrospraying technique for targeted delivery of docetaxel

Human epidermal growth factor receptor 2 (HER‐2) is overexpressed in 20–30% of human breast cancers, associated with poor prognosis and tumour aggression. The aim of this study was the production of trastuzumab‐targeted Ecoflex nanoparticles (NPs) loaded with docetaxel and in vitro evaluation of their cytotoxicity and cellular uptake. The NPs were manufactured by electrospraying and characterised regarding size, zeta potential, drug loading, and release behaviour. Then their cytotoxicity was evaluated by MTT assay against an HER‐2‐positive cell line, BT‐474, and an HER‐2‐negative cell line, MDA‐MB‐468. The cellular uptake was studied by flow cytometry and fluorescent microscope. The particle size of NPs was in an appropriate range, with relatively high drug entrapment and acceptable release efficiency. The results showed no cytotoxicity for the polymer, but the significant increment of cytotoxicity was observed by treatment with docetaxel‐loaded NPs in both HER‐2‐positive and HER‐2‐negative cell lines, in comparison with the free drug. The trastuzumab‐targeted NPs also significantly enhanced cytotoxicity against BT‐474 cells, compared with non‐targeted NPs.Inspec keywords: cancer, proteins, biomedical materials, nanofabrication, drug delivery systems, cellular biophysics, biological organs, nanomedicine, toxicology, tumours, nanoparticles, biomedical optical imaging, fluorescence, particle sizeOther keywords: human breast cancers, tumour aggression, trastuzumab‐targeted Ecoflex nanoparticles, cellular uptake, zeta potential drug loading, HER‐2‐positive cell line, HER‐2‐negative cell line, MDA‐MB‐468, particle size, trastuzumab‐conjugated nanoparticles, electrospraying technique, human epidermal growth factor receptor, cytotoxicity, nontargeted nanoparticles, butylene adipate‐co‐butylene terephthalate, trastuzumab‐targeted NP, docetaxel‐loaded NP     

Prognostic alternative splicing signature in cervical squamous cell carcinoma

Basing on alternative splicing events (ASEs) databases, the authors herein aim to explore potential prognostic biomarkers for cervical squamous cell carcinoma (CESC). mRNA expression profiles and relevant clinical data of 223 patients with CESC were obtained from The Cancer Genome Atlas (TCGA). Correlated genes, ASEs and percent‐splice‐in (PSI) were downloaded from SpliceSeq, respectively. The PSI values of survival‐associated alternative splicing events (SASEs) were used to construct the basis of a prognostic index (PI). A protein–protein interaction (PPI) network of genes related to SASEs was generated by STRING and analysed with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Consequently, 41,776 ASEs were discovered in 19,724 genes, 2596 of which linked with 3669 SASEs. The PPI network of SASEs related genes revealed that TP53 and UBA52 were core genes. The low‐risk group had a longer survival period than high‐risk counterparts, both groups being defined according to PI constructed upon the top 20 splicing events or PI on the overall splicing events. The AUC value of ROC reached up to 0.88, demonstrating the prognostic potential of PI in CESC. These findings suggested that ASEs involve in the pathogenesis of CESC and may serve as promising prognostic biomarkers for this female malignancy.Inspec keywords: gynaecology, molecular biophysics, genomics, proteins, cellular biophysics, genetics, medical computing, cancer, ontologies (artificial intelligence), RNAOther keywords: protein‐protein interaction network, CESC pathogenesis, gene ontology, Kyoto‐encyclopedia‐of‐genes‐and‐genomes, SASEs related genes, PPI network, survival‐associated alternative splicing events, PSI values, percent‐splice‐in, Cancer Genome Atlas, mRNA expression profiles, prognostic biomarkers, alternative splicing events databases, cervical squamous cell carcinoma, prognostic alternative splicing signature     

Multi‐threshold and multi‐input DNA logic design style for profiling the microRNA biomarkers of real cancers

Early detection of cancer is very critical because it can reduce the treatment risk and cost. MicroRNAs (miRNAs) have been introduced in recent years as an efficient class of biomarkers for cancer early detection. Now, real‐time polymerase chain reaction has been used to profile the miRNA expression, which is costly, time consuming and low accuracy. Most recently, DNA logic gates are used to detect the miRNA expression level that is more accurate and faster than previous methods. The DNA‐based logic gates face with serious challenges such as the large complexity and low scalability. In this study, the authors proposed a methodology to design multi‐threshold and multi‐input DNA‐based logic gates in response to specific miRNA inputs in live mammalian cells. The proposed design style can simultaneously recognise multiple miRNAs with different rising and falling thresholds. The design style has been evaluated on the lung cancer biomarkers and the experimental results show the efficiency of the proposed method in terms of accuracy, efficiency and speed.Inspec keywords: DNA, logic design, biocomputing, RNA, molecular biophysics, logic gates, lung, genetics, cellular biophysics, cancer, biology computing, enzymes, biosensorsOther keywords: falling thresholds, specific miRNA inputs, multiinput DNA‐based logic gates, low scalability, DNA‐based logic gates face, miRNA expression level, DNA logic gates, low accuracy, time consuming, real‐time polymerase chain reaction, cancer early detection, treatment risk, cancers, microRNA biomarkers, multiinput DNA logic design style, multithreshold, lung cancer biomarkers     

Synthesis of surfactant‐modified ZIF‐8 with controllable microstructures and their drug loading and sustained release behaviour

Metal‐organic frameworks (MOFs) as drug carriers have many advantages than traditional drug carriers and have received extensive attention from researchers. However, how to regulate the microstructure of MOFs to improve the efficiency of drug delivery and sustained release behaviour is still a big problem for the clinical application. Herein, the authors synthesise surfactant‐modified ZIF‐8 nanoparticles with different microstructures by using different types of surfactants to modify ZIF‐8. The surfactant‐modified ZIF‐8 nanoparticles have the larger specific surface area and total micropore volumes than the original ZIF‐8, which enables doxorubicin (DOX) to be more effectively loaded on the drug carriers and achieve controlled drug sustained release. Excellent degradation performance of ZIF‐8 nanoparticles facilitates the metabolism of drug carriers. The formulation was evaluated for cytotoxicity, cellular uptake and intracellular location in the A549 human non‐small‐cell lung cancer cell line. ZIF‐8/DOX nano drugs exhibit higher cytotoxicity towards cells in comparison with free DOX, suggesting the potential application in nano drugs to cancer chemotherapy.Inspec keywords: nanomedicine, lung, nanofabrication, drug delivery systems, cellular biophysics, nanoparticles, cancer, toxicology, biomedical materials, drugs, organometallic compounds, surfactants, porosity, biodegradable materialsOther keywords: controlled drug sustained release, nanodrugs, controllable microstructures, drug loading, metal‐organic frameworks, traditional drug carriers, drug delivery, surfactant‐modified ZIF‐8 nanoparticles, specific surface area, micropore volumes, doxorubicin, degradation performance, metabolism, cytotoxicity, cellular uptake, intracellular location, A549 human nonsmall‐cell lung cancer cell line, cancer chemotherapy