Gene set correlation enrichment analysis for interpreting and annotating gene expression profiles.

Pathway analysis, including nontopology-based (non-TB) and topology-based (TB) methods, is widely used to interpret the biological phenomena underlying differences in expression data between two phenotypes. By considering dependencies and interactions between genes, TB methods usually perform better than non-TB methods in identifying pathways that include closely relevant or directly causative genes for a given phenotype. However, most TB methods may be limited by incomplete pathway data used as the reference network or by difficulties in selecting appropriate reference networks for different research topics. Here, we propose a gene set correlation enrichment analysis method, Gscore, based on an expression dataset-derived coexpression network to examine whether a differentially expressed gene (DEG) list (or each of its DEGs) is associated with a known gene set. Gscore is better able to identify target pathways in 89 human disease expression datasets than eight other state-of-the-art methods and offers insight into how disease-wide and pathway-wide associations reflect clinical outcomes. When applied to RNA-seq data from COVID-19-related cells and patient samples, Gscore provided a means for studying how DEGs are implicated in COVID-19-related pathways. In summary, Gscore offers a powerful analytical approach for annotating individual DEGs, DEG lists, and genome-wide expression profiles based on existing biological knowledge.

SWEET: a single-sample network inference method for deciphering individual features in disease.

Recently, extracting inherent biological system information (e.g. cellular networks) from genome-wide expression profiles for developing personalized diagnostic and therapeutic strategies has become increasingly important. However, accurately constructing single-sample networks (SINs) to capture individual characteristics and heterogeneity in disease remains challenging. Here, we propose a sample-specific-weighted correlation network (SWEET) method to model SINs by integrating the genome-wide sample-to-sample correlation (i.e. sample weights) with the differential network between perturbed and aggregate networks. For a group of samples, the genome-wide sample weights can be assessed without prior knowledge of intrinsic subpopulations to address the network edge number bias caused by sample size differences. Compared with the state-of-the-art SIN inference methods, the SWEET SINs in 16 cancers more likely fit the scale-free property, display higher overlap with the human interactomes and perform better in identifying three types of cancer-related genes. Moreover, integrating SWEET SINs with a network proximity measure facilitates characterizing individual features and therapy in diseases, such as somatic mutation, mut-driver and essential genes. Biological experiments further validated two candidate repurposable drugs, albendazole for head and neck squamous cell carcinoma (HNSCC) and lung adenocarcinoma (LUAD) and encorafenib for HNSCC. By applying SWEET, we also identified two possible LUAD subtypes that exhibit distinct clinical features and molecular mechanisms. Overall, the SWEET method complements current SIN inference and analysis methods and presents a view of biological systems at the network level to offer numerous clues for further investigation and clinical translation in network medicine and precision medicine.

TBC1D10B promotes tumor progression in colon cancer via PAK4­mediated promotion of the PI3K/AKT/mTOR pathway.

This study aimed to explore the expression, function, and mechanisms of TBC1D10B in colon cancer, as well as its potential applications in the diagnosis and treatment of the disease.The expression levels of TBC1D10B in colon cancer were assessed by analyzing the TCGA and CCLE databases. Immunohistochemistry analysis was conducted using tumor and adjacent non-tumor tissues from 68 colon cancer patients. Lentiviral infection techniques were employed to silence and overexpress TBC1D10B in colon cancer cells. The effects on cell proliferation, migration, and invasion were evaluated using CCK-8, EDU, wound healing, and Transwell invasion assays. Additionally, GSEA enrichment analysis was used to explore the association of TBC1D10B with biological pathways related to colon cancer. TBC1D10B was significantly upregulated in colon cancer and closely associated with patient prognosis. Silencing of TBC1D10B notably inhibited proliferation, migration, and invasion of colon cancer cells and promoted apoptosis. Conversely, overexpression of TBC1D10B enhanced these cellular functions. GSEA analysis revealed that TBC1D10B is enriched in the AKT/PI3K/mTOR signaling pathway and highly correlated with PAK4. The high expression of TBC1D10B in colon cancer is associated with poor prognosis. It influences cancer progression by regulating the proliferation, migration, and invasion capabilities of colon cancer cells, potentially acting through the AKT/PI3K/mTOR signaling pathway. These findings provide new targets and therapeutic strategies for the treatment of colon cancer.

Deep-computer-generated holography with temporal-focusing and a digital propagation matrix for rapid 3D multiphoton stimulation.

Deep learning-based computer-generated holography (DeepCGH) has the ability to generate three-dimensional multiphoton stimulation nearly 1,000 times faster than conventional CGH approaches such as the Gerchberg-Saxton (GS) iterative algorithm. However, existing DeepCGH methods cannot achieve axial confinement at the several-micron scale. Moreover, they suffer from an extended inference time as the number of stimulation locations at different depths (i.e., the number of input layers in the neural network) increases. Accordingly, this study proposes an unsupervised U-Net DeepCGH model enhanced with temporal focusing (TF), which currently achieves an axial resolution of around 5 µm. The proposed model employs a digital propagation matrix (DPM) in the data preprocessing stage, which enables stimulation at arbitrary depth locations and reduces the computation time by more than 35%. Through physical constraint learning using an improved loss function related to the TF excitation efficiency, the axial resolution and excitation intensity of the proposed TF-DeepCGH with DPM rival that of the optimal GS with TF method but with a greatly increased computational efficiency.

Functionalized magnetic particles coupled with LC-MS strategy facilitated discovery of trace thioalkaloids with potent immunosuppressive activity.

Trace natural products (TNPs) are still the vital source of drug development. However, the mining of novel TNPs is becoming increasingly challenging due to their low abundance and complex interference. A comprehensive strategy was proposed in which the functionalized magnetic particles integrated with LC-MS for TNPs discovery. Under the guidance of the approach, fifteen trace Nuphar alkaloids including seven new ones, cyanopumiline A sulfoxide (1), cyanopumiline C sulfoxide (8) and cyanopumilines A-E (4-5, 10, 12-13) featuring an undescribed nitrile-containing 6/6/5/6/6 pentacyclic ring system were isolated from the rhizomes of Nuphar pumila. Their structures and absolute configurations were determined on the basis of detailed spectroscopic data analysis and single-crystal X-ray diffraction analysis. Notably, a concise method based on 13C NMR spectroscopy was established to determine the relative configurations of spiroatoms. Biologically, compounds 1-12 exhibited potent immunosuppressive activities with IC50 values ranging from 0.1-12.1 µM against anti-CD3/CD28 induced human peripheral T cell proliferation. Mechanistic studies revealed that 4 could dose-dependently decrease pro-inflammatory cytokines and the expression levels of CD25 and CD71.

Epidemiology and outcomes of multidrug-resistant bacterial infection in non-cystic fibrosis bronchiectasis.

PURPOSE: Multidrug-resistant (MDR) bacteria impose a considerable health-care burden and are associated with bronchiectasis exacerbation. This study investigated the clinical outcomes of adult patients with bronchiectasis following MDR bacterial infection. METHODS: From the Chang Gung Research Database, we identified patients with bronchiectasis and MDR bacterial infection from 2008 to 2017. The control group comprised patients with bronchiectasis who did not have MDR bacterial infection and were propensity-score matched at a 1:2 ratio. The main outcomes were in-hospital and 3-year mortality. RESULTS: In total, 554 patients with both bronchiectasis and MDR bacterial infection were identified. The types of MDR bacteria that most commonly affected the patients were MDR- Acinetobacter baumannii (38.6%) and methicillin-resistant Staphylococcus aureus (18.4%), Extended-spectrum-beta-lactamases (ESBL)- Klebsiella pneumoniae (17.8%), MDR-Pseudomonas (14.8%), and ESBL-E. coli (7.5%). Compared with the control group, the MDR group exhibited lower body mass index scores, higher rate of chronic bacterial colonization, a higher rate of previous exacerbations, and an increased use of antibiotics. Furthermore, the MDR group exhibited a higher rate of respiratory failure during hospitalization (MDR vs. control, 41.3% vs. 12.4%; p < 0.001). The MDR and control groups exhibited in-hospital mortality rates of 26.7% and 7.6%, respectively (p < 0.001); 3-year respiratory failure rates of 33.5% and 13.5%, respectively (p < 0.001); and 3-year mortality rates of 73.3% and 41.5%, respectively (p < 0.001). After adjustments were made for confounding factors, the infection with MDR and MDR bacteria species were determined to be independent risk factors affecting in-hospital and 3-year mortality. CONCLUSIONS: MDR bacteria were discovered in patients with more severe bronchiectasis and were independently associated with an increased risk of in-hospital and 3-year mortality. Given our findings, we recommend that clinicians identify patients at risk of MDR bacterial infection and follow the principle of antimicrobial stewardship to prevent the emergence of resistant bacteria among patients with bronchiectasis.

Enhancing indicator condition-guided HIV testing in Taiwan: a nationwide case-control study from 2009 to 2015.

BACKGROUND: Although indicator condition (IC)-guided HIV testing (IC-HIVT) is effective at facilitating timely HIV diagnosis, research on IC categories and the related HIV risk in Taiwan is limited. To improve the adoption and spread of IC-HIVT in Taiwan, this study compared the IC categories of people living with HIV (PLWH) and non-HIV controls and investigated delays in the diagnosis of HIV infection. METHODS: This nationwide, retrospective, 1:10-matched case-control study analyzed data from the Notifiable Diseases Surveillance System and National Health Insurance Research Database to evaluate 42 ICs for the 5-year period preceding a matched HIV diagnostic date from 2009 to 2015. The ICs were divided into category 1 ICs (AIDS-defining opportunistic illnesses [AOIs]), category 2 ICs (diseases associated with impaired immunity or malignancy but not AOIs), category 3 ICs (ICs associated with sexual behaviors), and category 4 ICs (mononucleosis or mononucleosis-like syndrome). Logistic regression was used to evaluate the HIV risk associated with each IC category (at the overall and annual levels) before the index date. Wilcoxon rank-sum test was performed to assess changes in diagnostic delays following an incident IC category by HIV transmission routes. RESULTS: Fourteen thousand three hundred forty-seven PLWH were matched with 143,470 non-HIV controls. The prevalence results for all ICs and category 1-4 ICs were, respectively, 42.59%, 11.16%, 15.68%, 26.48%, and 0.97% among PLWH and 8.73%, 1.05%, 4.53%, 3.69%, and 0.02% among non-HIV controls (all P < 0.001). Each IC category posed a significantly higher risk of HIV infection overall and annually. The median (interquartile range) potential delay in HIV diagnosis was 15 (7-44), 324.5 (36-947), 234 (13-976), and 74 (33-476) days for category 1-4 ICs, respectively. Except for category 1 for men who have sex with men, these values remained stable across 2009-2015, regardless of the HIV transmission route. CONCLUSIONS: Given the ongoing HIV diagnostic delay, IC-HIVT should be upgraded and adapted to each IC category to enhance early HIV diagnosis.

New caffeoyl derivatives with potent DPPH radical scavenging activity from Elephantopus tomentosus.

Eight new caffeoyl derivatives, elephantomentosides A-H (1 - 8), together with ten known ones (9 - 18), were isolated from the whole plant of Elephantopos tomentosus L. Their structures were elucidated using detailed spectroscopic analysis. Structurally, compounds 1 - 8 are composed of ß-D-glucopyranose, and almost all of the substituent positions are at the C-1' and C-4' of glucopyranose. The anti-inflammatory and antioxidant activities of all isolated compounds were evaluated in vitro. Compounds 9-10, 13-15, and 17-18 exhibited significant DPPH scavenging capacity with IC50 values in the range of 10.01-25.07 µM, in comparison with Vc (IC50, 17.98 µM).

Temporal-Focusing Multiphoton Excitation Single-Molecule Localization Microscopy Using Spontaneously Blinking Fluorophores.

Single-molecule localization microscopy (SMLM) based on temporal-focusing multiphoton excitation (TFMPE) and single-wavelength excitation is used to visualize the three-dimensional (3D) distribution of spontaneously blinking fluorophore-labeled subcellular structures in a thick specimen with a nanoscale-level spatial resolution. To eliminate the photobleaching effect of unlocalized molecules in out-of-focus regions for improving the utilization rate of the photon budget in 3D SMLM imaging, SMLM with single-wavelength TFMPE achieves wide-field and axially confined two-photon excitation (TPE) of spontaneously blinking fluorophores. TPE spectral measurement of blinking fluorophores is then conducted through TFMPE imaging at a tunable excitation wavelength, yielding the optimal TPE wavelength for increasing the number of detected photons from a single blinking event during SMLM. Subsequently, the TPE fluorescence of blinking fluorophores is recorded to obtain a two-dimensional TFMPE-SMLM image of the microtubules in cancer cells with a localization precision of 18±6 nm and an overall imaging resolution of approximately 51 nm, which is estimated based on the contribution of Nyquist resolution and localization precision. Combined with astigmatic imaging, the system is capable of 3D TFMPE-SMLM imaging of brain tissue section of a 5XFAD transgenic mouse with the pathological features of Alzheimer's disease, revealing the distribution of neurotoxic amyloid-beta peptide deposits.

Obesity as a clinical predictor for severe manifestation of dengue: a systematic review and meta-analysis.

BACKGROUND: Severe dengue often leads to poor clinical outcomes and high mortality; as a result, it is of vital importance to find prognostic factors associated with the severe form of dengue. Obesity is known to deteriorate many infectious diseases due to impaired immune responses. Several studies have suggested that obese patients with dengue infection tend to have more severe manifestations with poorer prognosis. However, a firm conclusion could not be drawn due to the varied results of these studies. Here, we aimed to conduct a systematic review and meta-analysis to investigate the association between obesity and dengue severity. METHODS: A literature search for relevant studies was conducted in PubMed, Embase, Ovid Medline and Cochrane from inception to September 9, 2022. The two main keywords were "dengue" and "obesity". Mantel-Haenszel method and random effects model was used to analyze the pooled odds ratio with 95% confidence intervals. RESULTS: A total of 15 article involving a total of 6,508 patients were included in the meta-analysis. Included patients in most studies were hospitalized pediatric patients. Only one study included adulthood data. Three cohort studies, four case-control studies, and one cross-sectional studies found a significant association between obesity and dengue severity. In contrast, three cohort studies, three case-control studies, and one cross-sectional study reported no significant relationship between obesity and dengue severity. Our analysis results showed that patient with obesity is 50% (OR = 1.50; 95%CI: 1.15-1.97) more likely to develop severe manifestation of dengue. CONCLUSION: This meta-analysis revealed that overweight could be a clinical predictor for severe disease for pediatric patients with dengue infection.

Investigating the effects of Ceylon cinnamon water extract on HepG2 cells for Type 2 diabetes therapy.

Cinnamon and its extracts have been used as herbal remedies for many ailments, including for reducing insulin resistance and diabetes complications. Type 2 diabetes mellitus (T2DM) is a rapidly growing health concern around the world. Although many drugs are available for T2DM treatment, side effects and costs can be considerable, and there is increasing interest in natural products for managing chronic health conditions. Cinnamon may decrease the expression of genes associated with T2DM risk. The purpose of this study was to evaluate the effects of cinnamon water extract (CWE) compared with metformin on T2DM-related gene expression. HepG2 human hepatoma cells, widely used in drug metabolism and hepatotoxicity studies, were treated with different concentrations of metformin or CWE for 24 or 48 h. Cell viability was assessed by MTT (3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium) assay and glucose uptake was compared in untreated and CWE- or metformin-treated cells under high-glucose conditions. Finally, total RNA was extracted and analyzed by RNA sequencing (RNA-seq), and bioinformatics analyses were performed to compare the transcriptional effects of CWE and metformin. We found cell viability was better in cells treated with CWE than in metformin-treated cells, demonstrating that CWE was not toxic at tested doses. CWE significantly increased glucose uptake in HepG2 cells, to the same degree as metformin (1.4-fold). RNA-seq data revealed CWE and metformin both induced significantly increased (1.3- to 1.4-fold) glucose uptake gene expression compared with untreated controls. Transcriptional differences between CWE and metformin were not significant. The effects of 0.125 mg mL-1 CWE on gene expression were comparable to 1.5 mg mL-1 (9.5 mM) metformin. In addition, gene expression at 0.125 mg mL-1 CWE was comparable to 1.5 mg mL-1 (9.5 mM) metformin. Our results reveal that CWE's effects on cell viability, glucose uptake, and gene expression in HepG2 cells are comparable to those of metformin, suggesting CWE may be an effective dietary supplement for mitigating T2DM-related metabolic dysfunction.

High-throughput quantitative microscopy-based half-life measurements of intravenously injected agents.

Accurate analysis of blood concentration and circulation half-life is an important consideration for any intravenously administered agent in preclinical development or for therapeutic application. However, the currently available tools to measure these parameters are laborious, expensive, and inefficient for handling multiple samples from complex multivariable experiments. Here we describe a robust high-throughput quantitative microscopy-based method to measure the blood concentration and circulation half-life of any fluorescently labeled agent using only a small (2 µL) amount of blood volume, enabling additional end-point measurements to be assessed in the same subject. To validate this method, we demonstrate its use to measure the circulation half-life in mice of two types of fluorescently labeled polymeric nanoparticles of different sizes and surface chemistries and of a much smaller fluorescently labeled monoclonal antibody. Furthermore, we demonstrate the improved accuracy of this method compared to previously described methods.

Effects of transjugular intrahepatic portosystemic shunt on abdominal muscle mass in patients with decompensated cirrhosis.

BACKGROUND: Sarcopenia is a common finding in patients with decompensated cirrhosis without effective therapy. We aimed to examine whether a transjugular portosystemic shunt (TIPS) could improve the abdominal muscle mass assessed by cross-sectional images in patients with decompensated cirrhosis and to investigate the association of imaging-defined sarcopenia with the prognosis of such patients. METHODS: In this retrospective observational study, we enrolled 25 Decompensated cirrhosis patients aged >20 who received TIPS for the control of variceal bleeding or refractory ascites between April 2008 and April 2021. All of them underwent preoperative computed tomography or magnetic resonance imaging, which was used to determine psoas muscle (PM) and paraspinal muscle (PS) indices at the third lumbar vertebra. First, we compared baseline muscle mass with muscle mass at 6 and 12 months after TIPS placement and analyzed PM- and PS-defined sarcopenia to predict mortality. RESULTS: Among 25 patients, 20 (80.0%) and 12 (48.0%) had PM- and PS-defined sarcopenia, respectively, at baseline. In total, 16 and 8 patients were followed up for 6 and 12 months, respectively. All imaging-based muscle measurements performed 12 months after TIPS placement were significantly greater than the baseline measurements (all p < 0.05). Unlike patients with PS-defined sarcopenia (p = 0.529), patients with PM-defined sarcopenia had poorer survival than did patients without (p = 0.036). CONCLUSION: PM mass in patients with decompensated cirrhosis may increase by 6 or 12 months after TIPS placement and imply a better prognosis. Patients with preoperative PM-defined sarcopenia may suggest poorer survival.

Identification of the HNSC88 Molecular Signature for Predicting Subtypes of Head and Neck Cancer.

Head and neck squamous cell carcinoma (HNSC) exhibits genetic heterogeneity in etiologies, tumor sites, and biological processes, which significantly impact therapeutic strategies and prognosis. While the influence of human papillomavirus on clinical outcomes is established, the molecular subtypes determining additional treatment options for HNSC remain unclear and inconsistent. This study aims to identify distinct HNSC molecular subtypes to enhance diagnosis and prognosis accuracy. In this study, we collected three HNSC microarrays (n = 306) from the Gene Expression Omnibus (GEO), and HNSC RNA-Seq data (n = 566) from The Cancer Genome Atlas (TCGA) to identify differentially expressed genes (DEGs) and validate our results. Two scoring methods, representative score (RS) and perturbative score (PS), were developed for DEGs to summarize their possible activation functions and influence in tumorigenesis. Based on the RS and PS scoring, we selected candidate genes to cluster TCGA samples for the identification of molecular subtypes in HNSC. We have identified 289 up-regulated DEGs and selected 88 genes (called HNSC88) using the RS and PS scoring methods. Based on HNSC88 and TCGA samples, we determined three HNSC subtypes, including one HPV-associated subtype, and two HPV-negative subtypes. One of the HPV-negative subtypes showed a relationship to smoking behavior, while the other exhibited high expression in tumor immune response. The Kaplan-Meier method was used to compare overall survival among the three subtypes. The HPV-associated subtype showed a better prognosis compared to the other two HPV-negative subtypes (log rank, p = 0.0092 and 0.0001; hazard ratio, 1.36 and 1.39). Additionally, within the HPV-negative group, the smoking-related subgroup exhibited worse prognosis compared to the subgroup with high expression in immune response (log rank, p = 0.039; hazard ratio, 1.53). The HNSC88 not only enables the identification of HPV-associated subtypes, but also proposes two potential HPV-negative subtypes with distinct prognoses and molecular signatures. This study provides valuable strategies for summarizing the roles and influences of genes in tumorigenesis for identifying molecular signatures and subtypes of HNSC.

Postoperative Stroke After Type A Aortic Dissection Repair: Hemorrhage Versus Ischemia.

BACKGROUND: Postoperative stroke is a severe and potentially disabling complication following surgical intervention for acute type A aortic dissection (ATAAD). This retrospective study aims to compare the early and late outcomes between patients who had hemorrhagic and ischemic stroke after undergoing ATAAD repair surgery. METHODS: Between January 2007 and June 2020, a total of 685 consecutive patients underwent ATAAD repair at our institution. Patients who had a preoperative stroke or were unconscious at presentation were excluded from this study. Of the 656 included for analysis, 102 (15.5%) patients had a postoperative stroke confirmed by computed tomography angiography. The strokes were classified into the ischemia group (n = 83, 12.7%) and hemorrhage group (n = 19, 2.9%). Clinical features, surgical information, postoperative complications, modified Rankin Scale (mRS) scores after discharge, and 5-year cumulative survival rates were compared. RESULTS: Demographics, comorbidities, and presentations of ATAAD were similar between the two groups, except a higher rate of preoperative antithrombotic medication was found in the hemorrhage group. The hemorrhage group was associated with a higher complexity of aortic arch replacement, longer cardiopulmonary bypass, and aortic clamping times than the ischemia group. A higher in-hospital mortality rate (42.1% versus 20.5%; p = 0.048) and a higher median mRS score at the 3-month follow-up after discharge (6[3-6] versus 4[2-6]; p = 0.027) were found in the hemorrhage group. The hemorrhage group showed a lower 5-year cumulative survival rate (23.4% versus 57.8%; p = 0.003) compared with the ischemia group. CONCLUSIONS: Postoperative hemorrhagic stroke was associated with poorer neurological outcomes and lower survival rates than those with ischemic stroke. Patients who have complex arch replacement, long cardiopulmonary bypass and aortic clamping times are at risk for postoperative hemorrhagic stroke and should have intensive neurological surveillance for early diagnosis and treatment after ATAAD repair surgery.

Microfluidic Co-culture Platforms for Studying Osteocyte Regulation of Other Cell Types under Dynamic Mechanical Stimulation.

PURPOSE OF REVIEW: Osteocytes are the most abundant cell type in bone. These unique cells act primarily as mechanosensors and play crucial roles in the functional adaptation of bone tissue. This review aims to summarize the recent microfluidic studies on mechanically stimulated osteocytes in regulating other cell types. RECENT FINDINGS: Microfluidics is a powerful technology that has been widely employed in recent years. With the advantages of microfluidic platforms, researchers can mimic multicellular environments and integrate dynamic systems to study osteocyte regulation under mechanical stimulation. Microfluidic platforms have been developed to investigate mechanically stimulated osteocytes in the direct regulation of multiple cell types, including osteoclasts, osteoblasts, and cancer cells, and in the indirect regulation of cancer cells via endothelial cells. Overall, these microfluidic studies foster the development of treatment approaches targeting osteocytes under mechanical stimulation.

New 11-Methoxymethylgermacranolides from the Whole Plant of Carpesium divaricatum.

Eight new 11-methoxymethylgermacranolides (1-8) were isolated from the ethanol extract of the whole plant of Carpesium divaricatum. The planar structures and relative configurations of the new compounds were determined by detailed spectroscopic analysis. The absolute configuration of 1 was established by electronic circular dichroism (ECD) spectrum and X-ray crystallographic analysis, and the stereochemistry of the new compounds 2-8 were determined by similar ECD data with 1. The absolute configurations of 5 and 7 were further confirmed by using quantum chemical electronic circular dichroism (ECD) calculations. Compound 4 exhibited weak cytotoxicity against MCF-7 cells. Compound 8 could potently decrease PGE2 productions in LPS-induced RAW 264.7 cells.

Weighted minimum feedback vertex sets and implementation in human cancer genes detection.

BACKGROUND: Recently, many computational methods have been proposed to predict cancer genes. One typical kind of method is to find the differentially expressed genes between tumour and normal samples. However, there are also some genes, for example, 'dark' genes, that play important roles at the network level but are difficult to find by traditional differential gene expression analysis. In addition, network controllability methods, such as the minimum feedback vertex set (MFVS) method, have been used frequently in cancer gene prediction. However, the weights of vertices (or genes) are ignored in the traditional MFVS methods, leading to difficulty in finding the optimal solution because of the existence of many possible MFVSs. RESULTS: Here, we introduce a novel method, called weighted MFVS (WMFVS), which integrates the gene differential expression value with MFVS to select the maximum-weighted MFVS from all possible MFVSs in a protein interaction network. Our experimental results show that WMFVS achieves better performance than using traditional bio-data or network-data analyses alone. CONCLUSION: This method balances the advantage of differential gene expression analyses and network analyses, improves the low accuracy of differential gene expression analyses and decreases the instability of pure network analyses. Furthermore, WMFVS can be easily applied to various kinds of networks, providing a useful framework for data analysis and prediction.

ReCGBM: a gradient boosting-based method for predicting human dicer cleavage sites.

BACKGROUND: Human dicer is an enzyme that cleaves pre-miRNAs into miRNAs. Several models have been developed to predict human dicer cleavage sites, including PHDCleav and LBSizeCleav. Given an input sequence, these models can predict whether the sequence contains a cleavage site. However, these models only consider each sequence independently and lack interpretability. Therefore, it is necessary to develop an accurate and explainable predictor, which employs relations between different sequences, to enhance the understanding of the mechanism by which human dicer cleaves pre-miRNA. RESULTS: In this study, we develop an accurate and explainable predictor for human dicer cleavage site - ReCGBM. We design relational features and class features as inputs to a lightGBM model. Computational experiments show that ReCGBM achieves the best performance compared to the existing methods. Further, we find that features in close proximity to the center of pre-miRNA are more important and make a significant contribution to the performance improvement of the developed method. CONCLUSIONS: The results of this study show that ReCGBM is an interpretable and accurate predictor. Besides, the analyses of feature importance show that it might be of particular interest to consider more informative features close to the center of the pre-miRNA in future predictors.

miRNAs derived from circulating small extracellular vesicles as diagnostic biomarkers for nasopharyngeal carcinoma.

The microRNAs (miRNAs) in circulating small extracellular vesicles (sEVs) have been suggested as potential biomarkers in cancer diagnosis. This study was designed to evaluate the circulating sEV-derived miRNAs as biomarkers for the diagnosis of nasopharyngeal carcinoma (NPC). We compared the miRNA profiles in plasma-derived sEVs between 16 patients with NPC and 5 healthy controls (HCs). A distinct set of miRNAs that were differentially expressed between patients with NPC and HCs was determined by means of integrative bioinformatics approaches. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway analysis revealed that the target genes of the differentially expressed miRNAs (DEMs) were mainly involved in cancer-associated signaling pathways. Seven representative DEMs were selected and further validated in an additional 60 patients with NPC and 40 HCs using quantitative reverse-transcription PCR analysis (qRT-PCR). Receiver operating characteristic (ROC) curve analysis was used to assess the accuracy of the sEV-miRNA-based model for diagnosis. The 3 miRNA-based model, comprising miR-134-5p, miR-205-5p, and miR-409-3p, showed good discriminating power with an area under the curve (AUC) value of 0.88 in the training set and 0.91 in the validation set. Furthermore, the diagnostic model had an excellent classification ability to distinguish patients with NPC at different clinical stages or Epstein-Barr virus infection status from HCs. In conclusion, our findings indicated that sEV-derived miRNA levels were altered in the plasma of patients with NPC in comparison with those in HCs. The model based on the 3 sEV-derived miRNAs could potentially act as an alternative or complementary approach for diagnosing NPC.