Neural-network based high-speed volumetric dynamic optical coherence tomography.

We demonstrate deep-learning neural network (NN)-based dynamic optical coherence tomography (DOCT), which generates high-quality logarithmic-intensity-variance (LIV) DOCT images from only four OCT frames. The NN model is trained for tumor spheroid samples using a customized loss function: the weighted mean absolute error. This loss function enables highly accurate LIV image generation. The fidelity of the generated LIV images to the ground truth LIV images generated using 32 OCT frames is examined via subjective image observation and statistical analysis of image-based metrics. Fast volumetric DOCT imaging with an acquisition time of 6.55 s/volume is demonstrated using this NN-based method.

Analysis of the synergistic benefits of typical technologies for pollution reduction and carbon reduction in the iron and steel industry in the Beijing-Tianjin-Hebei region.

With its high energy consumption and pollutant emissions, the iron and steel industry is a significant source of air pollution and carbon emissions in the Beijing-Tianjin-Hebei (BTH) region. To improve air quality and reduce greenhouse gas emissions, a series of policies involving ultra-low emission, synergistic reduction of pollution, and carbon application have been implemented in the region. This study has assessed air pollutant and CO2 emission patterns in the iron and steel industry of the region by employing co-control effects coordinate system, marginal abatement cost curve, and numerical modeling, along with the synergistic benefits of typical technologies. The results have demonstrated that: (1) the intensive production activities pertinent to iron and steel enterprises has contributed greatly to the emission in Tangshan and Handan, where the sintering process is the main source of SO2, NOx, PM2.5, and CO, accounting for 64.86%, 55.15%, 29.98%, and 46.43% of the total emissions, respectively. (2) Among the typical pollution control and reduction measures, industrial restructuring and adjustment of the energy-resource structure have led to the greatest effects on emission reduction. Technologies exhibiting great potential in emission reduction and high-cost efficiency such as Blast Furnace Top Gas Recovery Turbine Unit (TRT) need to be promoted. (3) In Tangshan city with the highest level of steel production, the iron and steel production activities contributed to the concentration of 30.51% of PM2.5, 50.67% of SO2, and 42.54% of NO2 during the non-heating period. During the heating period, pollutants pertinent to the combustion of fossil energy for heating have increased, while iron and steel induced emissions have decreased to 23.7%, 34.32%, and 29.13%, respectively. By 2030, it is speculated that the contribution of the iron and steel industry to air quality will be significantly decreased as result of successful implementation of ultra-low emission policies and typical synergistic reduction technologies.

Cardiac commitment driven by MyoD expression in pericardial stem cells.

Cellular therapy holds immense promise to remuscularize the damaged myocardium but is practically hindered by limited allogeneic sources of cardiac-committed cells that engraft stably in the recipient heart after transplantation. Here, we demonstrate that the pericardial tissue harbors myogenic stem cells (pSCs) that are activated in response to inflammatory signaling after myocardial infarction (MI). The pSCs derived from the MI rats (MI-pSCs) show in vivo and in vitro cardiac commitment characterized by cardiac-specific Tnnt2 expression and formation of rhythmic contraction in culture. Bulk RNA-seq analysis reveals significant upregulation of a panel of genes related to cardiac/myogenic differentiation, paracrine factors, and extracellular matrix in the activated pSCs compared to the control pSCs (Sham-pSCs). Notably, we define MyoD as a key factor that governs the process of cardiac commitment, as siRNA-mediated MyoD gene silencing results in a significant reduction of myogenic potential. Injection of the cardiac-committed cells into the infarcted rat heart leads to long-term survival and stable engraftment in the recipient myocardium. Therefore, these findings point to pericardial myogenic progenitors as an attractive candidate for cardiac cell-based therapy to remuscularize the damaged myocardium.

Cryo-EM structure of human O-GlcNAcylation enzyme pair OGT-OGA complex.

O-GlcNAcylation is a conserved post-translational modification that attaches N-acetyl glucosamine (GlcNAc) to myriad cellular proteins. In response to nutritional and hormonal signals, O-GlcNAcylation regulates diverse cellular processes by modulating the stability, structure, and function of target proteins. Dysregulation of O-GlcNAcylation has been implicated in the pathogenesis of cancer, diabetes, and neurodegeneration. A single pair of enzymes, the O-GlcNAc transferase (OGT) and O-GlcNAcase (OGA), catalyzes the addition and removal of O-GlcNAc on over 3,000 proteins in the human proteome. However, how OGT selects its native substrates and maintains the homeostatic control of O-GlcNAcylation of so many substrates against OGA is not fully understood. Here, we present the cryo-electron microscopy (cryo-EM) structures of human OGT and the OGT-OGA complex. Our studies reveal that OGT forms a functionally important scissor-shaped dimer. Within the OGT-OGA complex structure, a long flexible OGA segment occupies the extended substrate-binding groove of OGT and positions a serine for O-GlcNAcylation, thus preventing OGT from modifying other substrates. Conversely, OGT disrupts the functional dimerization of OGA and occludes its active site, resulting in the blocking of access by other substrates. This mutual inhibition between OGT and OGA may limit the futile O-GlcNAcylation cycles and help to maintain O-GlcNAc homeostasis.

CO2 emission accounting and emission reduction analysis of the steel production process based on the material-energy-carbon correlation effect.

This paper develops a process-level carbon emission calculation model for iron and steel enterprises through the carbon emission mechanism of the whole production process. The relationship between material, energy and carbon flows is considered and combined. The carbon emissions of enterprises are divided into industrial emissions and combustion emissions, and the indirect emissions of purchased intermediate products and electricity purchased from the grid are also considered. Carbon emission targets and corresponding emission reduction strategies are formulated at the enterprise and process levels. For example, consider an iron and steel enterprise. The different types of carbon emissions are accounted for, with their reduction potential analysed based on the carbon material flow analysis method. The results show that the carbon emission of this enterprise is 1930.87 kgCO2/t (CS), and the combustion emission caused by energy flow is the main contributor to the enterprise's carbon emission, accounting for 57.02% of the total emission. The carbon emission during iron-making accounts for 69.06% of the entire process and is critical in any carbon emission reduction of the enterprise. Among them, process emissions from the blast furnace process account for 81.79% of industrial emissions of the whole process, which is 356.51 kgCO2/t (CS), and is the main challenge of low carbon transformation in this extensive process. This study highlights that increasing the integrated steel-making scrap ratio and electric furnace steel production can break through the existing emission reduction limits. A 65.02% carbon emission reduction can be achieved, and using green electricity can reduce emissions by 24.15%. Reasonably determining the amount of purchased coke and paying attention to the high-value recycling of byproduct gas resources in the plant are essential to achieve low-carbon economic development of steel.

Blood typing and transfusion therapy in a patient with A2 subtype acute myeloid leukemia M2: A case report.

BACKGROUND: Acute myeloid leukemia (AML) is one of the most common types of leukemia in adults. However, AML is relatively rare in the population overall, accounting for only about 1 percent of all cancers. Treatment for AML can be very effective for some patients, yet it leaves others with serious and even life-threatening side effects. Chemotherapy is still the primary treatment for most AML, but over time, leukemia cells become resistant to chemotherapy drugs. In addition, stem cell transplantation, targeted therapy, and immunotherapy are currently available. At the same time, with the progression of the disease, the patient may have corresponding complications, such as coagulation dysfunction, anemia, granulocytopenia, and repeated infection, so transfusion supportive therapy will be involved in the overall treatment regime. To date, few articles have reported on blood transfusion treatment options for patients with ABO subtypes AML-M2. Blood transfusion therapy is an important supportive treatment for AML-M2, and accurate determination of patients' blood type is one of the most important steps in the treatment process. In this study, we explored blood typing and supportive treatment strategies for a patient with A2 subtype AML-M2 to provide the basis for treatment for all patients. CASE SUMMARY: In order to determine the blood type of the patient, serological and molecular biological methods were used for reference tests, and the genetic background was studied to determine the patient's final blood type and select the appropriate blood products for infusion treatment. According to the results obtained by serological and molecular biological methods, the blood type of the patient was A2 subtype; the genotype was A02/001; the irregular antibody screening was negative, and anti-A1 was found in the plasma. According to the overall treatment plan, active anti-infection, elevated cells, component blood transfusion support, and other rescue and supportive treatments were given, and the patient successfully passed the stage of myelosuppression after chemotherapy. Re-examination of bone marrow smears showed that AL was in complete remission of bone marrow signs, and minimal residual leukemia lesions suggested no cells with obvious abnormal immunophenotype (residual leukemia cells < 10-4). CONCLUSION: The infusion of patients with A2 subtype AML-M2 with A irradiated platelets and O washing red blood cells can meet the needs of clinical treatment.

Identify potential driver genes for PAX-FOXO1 fusion-negative rhabdomyosarcoma through frequent gene co-expression network mining.

Background: Rhabdomyosarcoma (RMS) is a soft tissue sarcoma usually originated from skeletal muscle. Currently, RMS classification based on PAX-FOXO1 fusion is widely adopted. However, compared to relatively clear understanding of the tumorigenesis in the fusion-positive RMS, little is known for that in fusion-negative RMS (FN-RMS). Methods: We explored the molecular mechanisms and the driver genes of FN-RMS through frequent gene co-expression network mining (fGCN), differential copy number (CN) and differential expression analyses on multiple RMS transcriptomic datasets. Results: We obtained 50 fGCN modules, among which five are differentially expressed between different fusion status. A closer look showed 23% of Module 2 genes are concentrated on several cytobands of chromosome 8. Upstream regulators such as MYC, YAP1, TWIST1 were identified for the fGCN modules. Using in a separate dataset we confirmed that, comparing to FP-RMS, 59 Module 2 genes show consistent CN amplification and mRNA overexpression, among which 28 are on the identified chr8 cytobands. Such CN amplification and nearby MYC (also resides on one of the above cytobands) and other upstream regulators (YAP1, TWIST1) may work together to drive FN-RMS tumorigenesis and progression. Up to 43.1% downstream targets of Yap1 and 45.8% of the targets of Myc are differentially expressed in FN-RMS vs. normal comparisons, which also confirmed the driving force of these regulators. Discussion: We discovered that copy number amplification of specific cytobands on chr8 and the upstream regulators MYC, YAP1 and TWIST1 work together to affect the downstream gene co-expression and promote FN-RMS tumorigenesis and progression. Our findings provide new insights for FN-RMS tumorigenesis and offer promising targets for precision therapy. Experimental investigation about the functions of identified potential drivers in FN-RMS are in progress.

Study on the protective mechanism of dexmedetomidine on the liver of perioperative diabetic patients: A randomized controlled trial.

BACKGROUND: Although several studies have reported that dexmedetomidine is a highly selective α2-adrenergic receptor agonist that protects liver function in perioperative patients by inhibiting oxidative stress (OS) and inflammatory response, patients with type 2 diabetes mellitus (T2DM) have not been included in the previous studies. The purpose of this study was to investigate the effects of perioperative low-dose dexmedetomidine on perioperative liver function in T2DM patients. METHODS: This was a single-center, placebo-controlled randomized trial. Fifty-four T2DM patients scheduled for debridement of lower extremity ulcers were included in this study and randomly divided into 2 groups (n = 27 per group): the dexmedetomidine group (DEX group) and the control group (CON group). Continuous intravenous infusion of dexmedetomidine (DEX group) or normal saline (CON group) was administered from the completion of monitoring to the end of surgery. All participants received femoral and sciatic nerve block with 0.33% ropivacaine. The main result was the activity of liver enzymes (AST, ALT) reflecting liver function. The secondary results included variables reflecting blood glucose (Glu), blood lipids (TG, HDL, LDL, total cholesterol), biomarkers of OS (MDA, SOD), and systemic inflammatory response (TNF-α, IL-6). RESULTS: Compared with CON group, DEX group exhibited a reduction in hemodynamic parameters, Glu, systemic inflammatory response, and liver injury indicators. OS response MDA activity was lower in DEX group than in CON group, while SOD was higher than that in CON group. The variables reflecting lipid metabolism function showed no differences between the groups. CONCLUSION SUBSECTIONS: Dexmedetomidine administered perioperatively can reduce Glu levels and protect the liver by attenuating OS injury and inflammatory response in T2DM patients without any potential risk.

SPCS: a spatial and pattern combined smoothing method for spatial transcriptomic expression.

High-dimensional, localized ribonucleic acid (RNA) sequencing is now possible owing to recent developments in spatial transcriptomics (ST). ST is based on highly multiplexed sequence analysis and uses barcodes to match the sequenced reads to their respective tissue locations. ST expression data suffer from high noise and dropout events; however, smoothing techniques have the promise to improve the data interpretability prior to performing downstream analyses. Single-cell RNA sequencing (scRNA-seq) data similarly suffer from these limitations, and smoothing methods developed for scRNA-seq can only utilize associations in transcriptome space (also known as one-factor smoothing methods). Since they do not account for spatial relationships, these one-factor smoothing methods cannot take full advantage of ST data. In this study, we present a novel two-factor smoothing technique, spatial and pattern combined smoothing (SPCS), that employs the k-nearest neighbor (kNN) technique to utilize information from transcriptome and spatial relationships. By performing SPCS on multiple ST slides from pancreatic ductal adenocarcinoma (PDAC), dorsolateral prefrontal cortex (DLPFC) and simulated high-grade serous ovarian cancer (HGSOC) datasets, smoothed ST slides have better separability, partition accuracy and biological interpretability than the ones smoothed by preexisting one-factor methods. Source code of SPCS is provided in Github (https://github.com/Usos/SPCS).

Indisulam targets RNA splicing and metabolism to serve as a therapeutic strategy for high-risk neuroblastoma.

Neuroblastoma is the most common paediatric solid tumour and prognosis remains poor for high-risk cases despite the use of multimodal treatment. Analysis of public drug sensitivity data showed neuroblastoma lines to be sensitive to indisulam, a molecular glue that selectively targets RNA splicing factor RBM39 for proteosomal degradation via DCAF15-E3-ubiquitin ligase. In neuroblastoma models, indisulam induces rapid loss of RBM39, accumulation of splicing errors and growth inhibition in a DCAF15-dependent manner. Integrative analysis of RNAseq and proteomics data highlight a distinct disruption to cell cycle and metabolism. Metabolic profiling demonstrates metabolome perturbations and mitochondrial dysfunction resulting from indisulam. Complete tumour regression without relapse was observed in both xenograft and the Th-MYCN transgenic model of neuroblastoma after indisulam treatment, with RBM39 loss, RNA splicing and metabolic changes confirmed in vivo. Our data show that dual-targeting of metabolism and RNA splicing with anticancer indisulam is a promising therapeutic approach for high-risk neuroblastoma.

Distance correlation application to gene co-expression network analysis.

BACKGROUND: To construct gene co-expression networks, it is necessary to evaluate the correlation between different gene expression profiles. However, commonly used correlation metrics, including both linear (such as Pearson's correlation) and monotonic (such as Spearman's correlation) dependence metrics, are not enough to observe the nature of real biological systems. Hence, introducing a more informative correlation metric when constructing gene co-expression networks is still an interesting topic. RESULTS: In this paper, we test distance correlation, a correlation metric integrating both linear and non-linear dependence, with other three typical metrics (Pearson's correlation, Spearman's correlation, and maximal information coefficient) on four different arrays (macrophage and liver) and RNA-seq (cervical cancer and pancreatic cancer) datasets. Among all the metrics, distance correlation is distribution free and can provide better performance on complex relationships and anti-outlier. Furthermore, distance correlation is applied to Weighted Gene Co-expression Network Analysis (WGCNA) for constructing a gene co-expression network analysis method which we named Distance Correlation-based Weighted Gene Co-expression Network Analysis (DC-WGCNA). Compared with traditional WGCNA, DC-WGCNA can enhance the result of enrichment analysis and improve the module stability. CONCLUSIONS: Distance correlation is better at revealing complex biological relationships between gene profiles compared with other correlation metrics, which contribute to more meaningful modules when analyzing gene co-expression networks. However, due to the high time complexity of distance correlation, the implementation requires more computer memory.

TPSC: a module detection method based on topology potential and spectral clustering in weighted networks and its application in gene co-expression module discovery.

BACKGROUND: Gene co-expression networks are widely studied in the biomedical field, with algorithms such as WGCNA and lmQCM having been developed to detect co-expressed modules. However, these algorithms have limitations such as insufficient granularity and unbalanced module size, which prevent full acquisition of knowledge from data mining. In addition, it is difficult to incorporate prior knowledge in current co-expression module detection algorithms. RESULTS: In this paper, we propose a novel module detection algorithm based on topology potential and spectral clustering algorithm to detect co-expressed modules in gene co-expression networks. By testing on TCGA data, our novel method can provide more complete coverage of genes, more balanced module size and finer granularity than current methods in detecting modules with significant overall survival difference. In addition, the proposed algorithm can identify modules by incorporating prior knowledge. CONCLUSION: In summary, we developed a method to obtain as much as possible information from networks with increased input coverage and the ability to detect more size-balanced and granular modules. In addition, our method can integrate data from different sources. Our proposed method performs better than current methods with complete coverage of input genes and finer granularity. Moreover, this method is designed not only for gene co-expression networks but can also be applied to any general fully connected weighted network.

[Effects of chitosan oligosaccharide on alveolar bone resorption, Th17/Treg balance and OPG/RANKL/RANK pathway in periodontitis rats].

PURPOSE: To investigate the effect of chitosan oligosaccharide on alveolar bone resorption, Th17/Treg balance and OPG/RANKL/RANK pathway in rats with periodontitis. METHODS: Rat model of periodontitis was established, and the periodontitis rats were randomly divided into model group, low-dose chitosan oligosaccharide group, middle-dose chitosan oligosaccharide group, high-dose chitosan oligosaccharide group and metronidazole group, with 12 rats in each group, another 12 rats were set as control group. After treatment, gingival index and alveolar bone absorption were evaluated. H-E staining was used to observe the pathological changes of periodontal tissues. The ratio of Th17/Treg cells in peripheral blood was detected by flow cytometry, the levels of serum IL-17, TGF-ß, RANKL and OPG were detected by ELISA, and the expressions of OPG and RANKL mRNA in periodontal tissues of rats in each group were detected by real-time fluorescent quantitative PCR(qRT-PCR). SPSS 24.0 software package was used to analyze the data. RESULTS: Compared with the control group, the periodontal tissue of the model group showed periodontal membrane fiber bundle rupture, disordered arrangement, capillary expansion, proliferation, inflammatory cell infiltration and other pathological damage. Gingival index, alveolar bone resorption value, Th17/Treg ratio, serum RANKL and IL-17 levels, and periodontal RANKL mRNA level were significantly increased(P<0.05), while the levels of serum OPG, TGF-ß and OPG mRNA in periodontal tissues were significantly decreased (P<0.05). Compared with the model group, the pathological damage of periodontal tissue in the low-middle-and high-dose chitosan oligosaccharide groups and metronidazole group was reduced; gingival index, alveolar bone resorption value, Th17/Treg ratio, serum RANKL and IL-17 levels, and periodontal RANKL mRNA level were significantly decreased(P<0.05), while the levels of serum OPG, TGF-ß and OPG mRNA in periodontal tissues were significantly increased(P<0.05); there was a dose-dependent relationship between the chitosan oligosaccharide groups, and there was no significant difference between the high-dose chitosan oligosaccharide group and metronidazole group(P>0.05). CONCLUSIONS: Chitosan oligosaccharide can promote Th17/Treg balance to return to normal, up-regulate OPG expression, down-regulate RANKL expression, inhibit alveolar bone resorption in periodontitis rats and improve their clinical symptoms.

Mining TCGA database for prognostic genes in head and neck squamous cell carcinoma microenvironment.

BACKGROUND/PURPOSE: Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignant tumors. The aim of this study was to elucidate the effect of tumor microenvironment-related genes on the prognosis of HNSCC and to obtain tumor microenvironment-related genes that can predict poor prognosis in HNSCC patients. MATERIALS AND METHODS: The ESTIMATE algorithm was applied to the HNSCC transcriptomic data downloaded from the TCGA (The cancer genome atlas), and then the samples were divided into two groups: high and low immune scoring groups, and high and low basal scoring groups to screen for differentially expressed genes (DEGs) associated with poor patient outcomes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was performed to explore the potential functions of DEGs, and then to explore the potential prognostic value of individual DEGs. The results of survival analysis between DEGs and overall survival (OS) to explore tumor microenvironment-related genes relevant to the prognosis of HNSCC patients. RESULTS: Fifty-nine tumor microenvironment-related genes were screened for association of OS with HNSCC (P < 0.05). The GO and KEGG enrichment analysis showed that the selected DEGs may mediate immune response, extracellular matrix, and immunoglobulin binding via neutrophil activation in HNSCC. Six of these DEGs, GIMAP6, SELL, TIFAB, KCNA3, P2RY8 and CCR4 were most significantly associated with OS (P < 0.001). CONCLUSION: We identified six tumor microenvironment-related genes that were significantly associated with poor prognosis in HNSCC. These genes may inspire researchers to discover new targets and approaches for HNSCC treatment.

TPQCI: A topology potential-based method to quantify functional influence of copy number variations.

Copy number variation (CNV) is a major type of chromosomal structural variation that play important roles in many diseases including cancers. Due to genome instability, a large number of CNV events can be detected in diseases such as cancer. Therefore, it is important to identify the functionally important CNVs in diseases, which currently still poses a challenge in genomics. One of the critical steps to solve the problem is to define the influence of CNV. In this paper, we provide a topology potential based method, TPQCI, to quantify this kind of influence by integrating statistics, gene regulatory associations, and biological function information. We used this metric to detect functionally enriched genes on genomic segments with CNV in breast cancer and multiple myeloma and discovered biological functions influenced by CNV. Our results demonstrate that, by using our proposed TPQCI metric, we can detect disease-specific genes that are influenced by CNVs. Source codes of TPQCI are provided in Github (https://github.com/usos/TPQCI).

Effect of dynamic correlation on the ultrafast relaxation of uracil in the gas phase.

The photophysics and photochemistry of DNA/RNA nucleobases have been extensively investigated during the past two decades, both experimentally and theoretically. The ultrafast relaxation of the canonical nucleobases following photoexcitation is of significant interest when it comes to understanding how nature has ensured their photostability. Here we study the excited state dynamics of uracil which is a nucleobase found in RNA. Although theory and experiment have shed significant light on understanding the photoexcited dynamics of uracil, there are still disagreements in the literature about specific details. In order to examine how the dynamics is influenced by the underlying electronic structure theory, we have performed non-adiabatic excited state dynamics simulations of uracil using on-the-fly trajectory surface hopping methodology on potential energy surfaces calculated at different electronic structure theory levels (CASSCF, MRCIS, XMS-CASPT2, TD-DFT). These simulations reveal that the dynamics are very sensitive to the underlying electronic structure theory, with the multi-reference theory levels that include dynamic correlation, predicting that there is no trapping on the absorbing S2 state, in contrast to predictions from lower level electronic structure results. The dynamics are instead governed by ultrafast decay to the ground state, or trapping on the dark S1 state.

Long non-coding RNA FOXD2-AS1 promotes cell proliferation, metastasis and EMT in glioma by sponging miR-506-5p.

Long non-coding RNA forkhead box D2 adjacent opposite strand RNA 1 (FOXD2-AS1) has emerged as a potential oncogene in several tumors. However, its biological function and potential regulatory mechanism in glioma have not been fully investigated to date. In the present study, RT-qPCR was conducted to detect the levels of FOXD2-AS1 and microRNA (miR)-506-5p, and western blot assays were performed to measure the expression of CDK2, cyclinE1, P21, matrix metalloproteinase (MMP)7, MMP9, N-cadherin, E-cadherin and vimentin in glioma cells. A luciferase reporter assay was performed to verify the direct targeting of miR-506-5p by FOXD2-AS1. Subsequently, cell viability was analyzed using the CCK-8 assay. Cell migration and invasion were analyzed using Transwell and wound healing assays, respectively. The results demonstrated that FOXD2-AS1 was significantly overexpressed in glioma cells, particularly in U251 cells. Knockdown of FOXD2-AS1 in glioma cells significantly inhibited cell proliferation, migration, invasion and epithelial-mesenchymal transition (EMT) and regulated the expression of CDK2, cyclinE1, P21, MMP7 and MMP9. Next, a possible mechanism for these results was explored, and it was observed that FOXD2-AS1 binds to and negatively regulates miR-506-5p, which is known to be a tumor-suppressor gene in certain human cancer types. Furthermore, overexpression of miR-506-5p significantly inhibited cell proliferation, migration, invasion and EMT, and these effects could be reversed by transfecting FOXD2-AS1 into the cells. In conclusion, our data suggested that FOXD2-AS1 contributed to glioma proliferation, metastasis and EMT via competitively binding to miR-506-5p. FOXD2-AS1 may be a promising target for therapy in patients with glioma.

A pan-kidney cancer study identifies subtype specific perturbations on pathways with potential drivers in renal cell carcinoma.

BACKGROUND: Renal cell carcinoma (RCC) is a complex disease and is comprised of several histological subtypes, the most frequent of which are clear cell renal cell carcinoma (ccRCC), papillary renal cell carcinoma (PRCC) and chromophobe renal cell carcinoma (ChRCC). While lots of studies have been performed to investigate the molecular characterizations of different subtypes of RCC, our knowledge regarding the underlying mechanisms are still incomplete. As molecular alterations are eventually reflected on the pathway level to execute certain biological functions, characterizing the pathway perturbations is crucial for understanding tumorigenesis and development of RCC. METHODS: In this study, we investigated the pathway perturbations of various RCC subtype against normal tissue based on differential expressed genes within a certain pathway. We explored the potential upstream regulators of subtype-specific pathways with Ingenuity Pathway Analysis (IPA). We also evaluated the relationships between subtype-specific pathways and clinical outcome with survival analysis. RESULTS: In this study, we carried out a pathway-based analysis to explore the mechanisms of various RCC subtypes with TCGA RNA-seq data. Both commonly altered pathways and subtype-specific pathways were detected. To identify the distinctive characteristics of each subtype, we focused on subtype-specific perturbed pathways. Specifically, we observed that some of the altered pathways were regulated by several recurrent upstream regulators which presenting different expression patterns among distinct RCC subtypes. We also noticed that a large number of perturbed pathways were controlled by the subtype-specific upstream regulators. Moreover, we also evaluated the relationships between perturbed pathways and clinical outcome. Prognostic pathways were identified and their roles in tumor development and progression were inferred. CONCLUSIONS: In summary, we evaluated the relationships among pathway perturbations, upstream regulators and clinical outcome for differential subtypes in RCC. We hypothesized that the alterations of common upstream regulators as well as subtype-specific upstream regulators work together to affect the downstream pathway perturbations and drive cancer initialization and prognosis. Our findings not only increase our understanding of the mechanisms of various RCC subtypes, but also provide targets for personalized therapeutic intervention.

Downregulation of miR-484 is associated with poor prognosis and tumor progression of gastric cancer.

BACKGROUND: Gastric cancer is one of the most common cancers leading to high cancer mortality. MicroRNA-484 (miR-484) has been evaluated as a biomarker for various types of cancers. The subject of this study is to investigate the functional role of miR-484 in gastric cancer. METHODS: The expression of miR-484 in gastric cancer was analyzed by quantitative real-time polymerase chain reaction (qRT-PCR) assay. Kaplan-Meier survival and Cox regression analyses were employed to explore the prognostic significance of miR-484 in gastric cancer. The functional role of miR-484 in gastric cancer was determined by CCK-8 and Transwell assays. RESULTS: The results showed that miR-484 was significantly downregulated in gastric cancer tissues and cell lines. The downregulation of miR-484 was closely related to differentiation, lymph node metastasis, TNM stage, and poor prognosis. Cox regression analyses demonstrated that miR-484 was an independent prognosis indicator for gastric cancer patients. Additionally, the downregulation of miR-484 enhanced cell proliferation, migration, and invasion in gastric cancer cells. CONCLUSION: These data demonstrated that miR-484 can serve as a potential prognostic biomarker and therapeutic target for gastric cancer and it may be involved in the progression of gastric cancer.

Integration of molecular features with clinical information for predicting outcomes for neuroblastoma patients.

BACKGROUND: Neuroblastoma is one of the most common types of pediatric cancer. In current neuroblastoma prognosis, patients can be stratified into high- and low-risk groups. Generally, more than 90% of the patients in the low-risk group will survive, while less than 50% for those with the high-risk disease will survive. Since the so-called "high-risk" patients still contain patients with mixed good and poor outcomes, more refined stratification needs to be established so that for the patients with poor outcome, they can receive prompt and individualized treatment to improve their long-term survival rate, while the patients with good outcome can avoid unnecessary over treatment. METHODS: We first mined co-expressed gene modules from microarray and RNA-seq data of neuroblastoma samples using the weighted network mining algorithm lmQCM, and summarize the resulted modules into eigengenes. Then patient similarity weight matrix was constructed with module eigengenes using two different approaches. At the last step, a consensus clustering method called Molecular Regularized Consensus Patient Stratification (MRCPS) was applied to aggregate both clinical information (clinical stage and clinical risk level) and multiple eigengene data for refined patient stratification. RESULTS: The integrative method MRCPS demonstrated superior performance to clinical staging or transcriptomic features alone for the NB cohort stratification. It successfully identified the worst prognosis group from the clinical high-risk group, with less than 40% survived in the first 50 months of diagnosis. It also identified highly differentially expressed genes between best prognosis group and worst prognosis group, which can be potential gene biomarkers for clinical testing. CONCLUSIONS: To address the need for better prognosis and facilitate personalized treatment on neuroblastoma, we modified the recently developed bioinformatics workflow MRCPS for refined patient prognosis. It integrates clinical information and molecular features such as gene co-expression for prognosis. This clustering workflow is flexible, allowing the integration of both categorical and numerical data. The results demonstrate the power of survival prognosis with this integrative analysis workflow, with superior prognostic performance to only using transcriptomic data or clinical staging/risk information alone. REVIEWERS: This article was reviewed by Lan Hu, Haibo Liu, Julie Zhu and Aleksandra Gruca.