CRISPR-Cas9 screening develops an epigenetic and transcriptional gene signature for risk stratification and target prediction in neuroblastoma.

Objectives: Neuroblastoma (NB), a pediatric malignancy of the peripheral nervous system, is characterized by epigenetic and transcriptional (EP-TF) anomalies. This study aimed to develop an EP-TF clinical prognostic model for NB using CRISPR-Cas9 knockout screening. Results: An integrative analysis was conducted using CRISPR-Cas9 screening in vitro and in vivo with public NB datasets to identify 35 EP-TF genes that exhibited the highest expression in NB and were highly dependent on cancer viability. After univariate analysis, 27 of these 35 genes were included in the least absolute shrinkage and selection operator screen. We established and biologically validated a prognostic EP-TF model encompassing RUVBL1, LARP7, GTF3C4, THAP10, SUPT16H, TIGD1, SUV39H2, TAF1A, SMAD9, and FEM1B across diverse NB cohorts. MYCN serves a potential upstream regulator of EP-TF genes. The high-risk subtype exhibited traits associated with the malignant cell cycle, MYCN-linked signaling and chromatin remodeling, all of which are correlated with poor prognosis and immunosuppression. MEK inhibitors have emerged as promising therapeutic agents for targeting most EP-TF risk genes in NB. Conclusion: Our novel prognostic model shows significant potential for predicting and evaluating the overall survival of NB patients, offering insights into therapeutic targets.

Joint Extraction of Biomedical Events Based on Dynamic Path Planning Strategy and Hybrid Neural Network.

Biomedical event detection is a pivotal information extraction task in molecular biology and biomedical research, which provides inspiration for the medical search, disease prevention, and new drug development. The existing methods usually detect simple biomedical events and complex events with the same model, and the performance of the complex biomedical event extraction is relatively low. In this paper, we build different neural networks for simple and complex events respectively, which helps to promote the performance of complex event extraction. To avoid redundant information, we design dynamic path planning strategy for argument detection. To take full use of the information between the trigger identification and argument detection subtasks, and reduce the cascading errors, we build a joint event extraction model. Experimental results demonstrate our approach achieves the best F-score on the biomedical benchmark MLEE dataset and outperforms the recent state-of-the-art methods.

Multi-omics and pharmacological characterization of patient-derived glioma cell lines.

Glioblastoma (GBM) is the most common brain tumor and remains incurable. Primary GBM cultures are widely used tools for drug screening, but there is a lack of genomic and pharmacological characterization for these primary GBM cultures. Here, we collect 50 patient-derived glioma cell (PDGC) lines and characterize them by whole genome sequencing, RNA sequencing, and drug response screening. We identify three molecular subtypes among PDGCs: mesenchymal (MES), proneural (PN), and oxidative phosphorylation (OXPHOS). Drug response profiling reveals that PN subtype PDGCs are sensitive to tyrosine kinase inhibitors, whereas OXPHOS subtype PDGCs are sensitive to histone deacetylase inhibitors, oxidative phosphorylation inhibitors, and HMG-CoA reductase inhibitors. PN and OXPHOS subtype PDGCs stably form tumors in vivo upon intracranial transplantation into immunodeficient mice, whereas most MES subtype PDGCs fail to form tumors in vivo. In addition, PDGCs cultured by serum-free medium, especially long-passage PDGCs, carry MYC/MYCN amplification, which is rare in GBM patients. Our study provides a valuable resource for understanding primary glioma cell cultures and clinical translation and highlights the problems of serum-free PDGC culture systems that cannot be ignored.

Supercoiled DNA percentage: A key in-process control of linear DNA template for mRNA drug substance manufacturing.

The development of messenger RNA (mRNA) vaccines and therapeutics necessitates the production of high-quality in vitro-transcribed mRNA drug substance with specific critical quality attributes (CQAs), which are closely tied to the uniformity of linear DNA template. The supercoiled plasmid DNA is the precursor to the linear DNA template, and the supercoiled DNA percentage is commonly regarded as a key in-process control (IPC) during the manufacturing of linear DNA template. In this study, we investigate the influence of supercoiled DNA percentage on key mRNA CQAs, including purity, capping efficiency, double-stranded RNA (dsRNA), and distribution of poly(A) tail. Our findings reveal a significant impact of supercoiled DNA percentage on mRNA purity and in vitro transcription yield. Notably, we observe that the impact on mRNA purity can be mitigated through oligo-dT chromatography, alleviating the tight range of DNA supercoiled percentage to some extent. Overall, this study provides valuable insights into IPC strategies for DNA template chemistry, manufacturing, and controls (CMC) and process development for mRNA drug substance.

The correlation between anti-phospholipase A2 receptor antibodies and hypercoagulability in patients with idiopathic membranous nephropathy.

BACKGROUND: Patients with idiopathic membranous nephropathy (IMN) are more likely to be complicated by venous thromboembolism (VTE). The aim of the study was to investigate the potential association between anti-phospholipase A2 receptor (PLA2R) antibodies and hypercoagulability in patients with IMN. METHODS: A total of 168 patients with biopsy-proven IMN and 36 patients with biopsy-proven minimal change disease (MCD) were enrolled in this study. The clinical data, serum anti-PLA2R antibodies and coagulation-related indices of the patients were retrospectively analyzed. RESULTS: Patients with IMN were categorized into glomerular PLA2R staining-positive (GAg+) IMN group and glomerular PLA2R staining-negative (GAg-) IMN group in the study. Patients with IMN who were GAg + had lower PT, APTT and R time than patients with IMN who were GAg-, while the CI value was higher in patients with IMN who were GAg+. Patients with IMN who were GAg + were divided into the SAb+/GAg + group and the SAb-/GAg + group. Patients with IMN who were SAb+/GAg + had higher Fib and MA values than patients with IMN who were SAb-/GAg+. Correlation analysis showed that serum anti-PLA2R antibodies were positively correlated with fibrinogen, D-dimer, K time, CI value, α-angle, and MA value. Multiple linear regression analysis indicated that anti-PLA2R antibodies were independently correlated with fibrinogen and MA value. CONCLUSION: Our study provides a new perspective on the underlying mechanisms of hypercoagulability in patients with IMN. Anti-PLA2R antibodies are associated with hypercoagulability in patients with IMN and may affect coagulation in patients with IMN by affecting platelet aggregation function and fibrinogen counts.

Targeting Super-Enhancer-Driven Transcriptional Dependencies Suppresses Aberrant Hedgehog Pathway Activation and Overcomes Smoothened Inhibitor Resistance.

Aberrant activation of the Hedgehog (Hh) signaling pathway plays important roles in oncogenesis and therapeutic resistance in several types of cancer. The clinical application of FDA-approved Hh-targeted smoothened inhibitors (SMOi) is hindered by the emergence of primary or acquired drug resistance. Epigenetic and transcriptional-targeted therapies represent a promising direction for developing improved anti-Hh therapies. In this study, we integrated epigenetic/transcriptional-targeted small-molecule library screening with CRISPR/Cas9 knockout library screening and identified CDK9 and CDK12, two transcription elongation regulators, as therapeutic targets for antagonizing aberrant Hh activation and overcoming SMOi resistance. Inhibition of CDK9 or CDK12 potently suppressed Hh signaling and tumor growth in various SMOi responsive or resistant Hh-driven tumor models. Systemic epigenomic profiling elucidated the Hh-driven super-enhancer (SE) landscape and identified IRS1, encoding a critical component and cytoplasmic adaptor protein of the insulin-like growth factor (IGF) pathway, as an oncogenic Hh-driven SE target gene and effective therapeutic target in Hh-driven tumor models. Collectively, this study identifies SE-driven transcriptional dependencies that represent promising therapeutic vulnerabilities for suppressing the Hh pathway and overcoming SMOi resistance. As CDK9 and IRS inhibitors have already entered human clinical trials for cancer treatment, these findings provide comprehensive preclinical support for developing trials for Hh-driven cancers. Significance: Dissecting transcriptional dependencies driven by super-enhancers uncovers therapeutic targets in Hedgehog-driven cancers and identifies strategies for overcoming resistance to smoothened inhibitors.

Ascorbic acid-mediated reduction of arabinoxylan viscosity through free radical reactions.

Arabinoxylan (AX) is a potential natural food additive that can enhance the textural properties of food. However, the addition of ascorbic acid (AA) can easily lead to a decrease in the viscosity of AX, which poses a challenge in the development of AX-rich foods. Therefore, the purpose of this study is to elucidate the mechanisms behind the reduction in AX viscosity in the presence of AA. The results indicated that AA could reduce the apparent viscosity and molecular weight of AX without significantly affecting the monosaccharide composition, suggesting a potential mechanism related to the cleavage of AX glycosidic bonds. Interestingly, free radicals were present in the reaction system, and the generation of free radicals under different conditions was consistent with the reduction in apparent viscosity of AX. Furthermore, the reduction in AX apparent viscosity by AA was influenced by various factors including AA concentration, reaction time, temperature, pH, and metal ions. These findings suggested that the mechanism of AX degradation may be due to AA-induced free radical generation, leading to non-selective attacks on glycosidic bonds. Therefore, this study revealed that the potential mechanism behind the reduction in AX viscosity induced by AA involved the generation of ascorbic acid radicals.

Study on Interpretation Method of Multistage Fracture Tracer Flowback Curve in Tight Oil Reservoirs.

Multistage fracturing is widely used in the development of tight oil reservoirs, and the fine description of postfracturing fracture networks is a challenge in tight oil reservoir development. Based on the formation mechanism of dual-wing fractures and the principles of tracer flowback, a mathematical model for tracer concentration in dual-wing fractures is established by considering the convective diffusion of the tracer within the fractures. An interpretation method for tracer flowback curves, utilizing a combination of Gaussian fitting and theoretical equation inversion, is developed to provide a detailed description of fracture parameters such as fracture half-length, fracture width, and fracture conductivity in the postfracturing fracture network. This method can be rapidly applied in field practices. Application examples demonstrate that the relative errors between the calculated cumulative oil and water production using this method and the actual data are less than 5%, validating the accuracy and applicability of the established mathematical model for tracer flowback and the interpretation method for tracer concentration curves in addressing practical problems.

Depletion of CPNE7 sensitizes colorectal cancer to 5-fluorouracil by downregulating ATG9B expression.

We aimed to explore the biological function of CPNE7 and determine the impact of CPNE7 on chemotherapy resistance in colorectal cancer (CRC) patients. According to the Gene Expression Profiling Interactive Analysis database and previously published data, CPNE7 was identified as a potential oncogene in CRC. RT-qPCR and Western blotting were performed to verify the expression of CPNE7. Chi-square test was used to evaluate the associations between CPNE7 and clinical features. Cell proliferation, colony formation, cell migration and invasion, cell cycle and apoptosis were assessed to determine the effects of CPNE7. Transcriptome sequencing was used to identify potential downstream regulatory genes, and gene set enrichment analysis was performed to investigate downstream pathways. The effect of CPNE7 on 5-fluorouracil chemosensitivity was verified by half maximal inhibitory concentration (IC50). Subcutaneous tumorigenesis assay was used to examine the role of CPNE7 in sensitivity of CRC to chemotherapy in vivo. Transmission electron microscopy was used to detect autophagosomes. CPNE7 was highly expressed in CRC tissues, and its expression was correlated with T stage and tumour site. Knockdown of CPNE7 inhibited the proliferation and colony formation of CRC cells and promoted apoptosis. Knockdown of CPNE7 suppressed the expression of ATG9B and enhanced the sensitivity of CRC cells to 5-fluorouracil in vitro and in vivo. Knockdown of CPNE7 reversed the induction of the autophagy pathway by rapamycin and reduced the number of autophagosomes. Depletion of CPNE7 attenuated the malignant proliferation of CRC cells and enhanced the chemosensitivity of CRC cells to 5-fluorouracil.

Single-cell transcriptomic sequencing identifies subcutaneous patient-derived xenograft recapitulated medulloblastoma.

BACKGROUND: Medulloblastoma (MB) is one of the most common malignant brain tumors that mainly affect children. Various approaches have been used to model MB to facilitate investigating tumorigenesis. This study aims to compare the recapitulation of MB between subcutaneous patient-derived xenograft (sPDX), intracranial patient-derived xenograft (iPDX), and genetically engineered mouse models (GEMM) at the single-cell level. METHODS: We obtained primary human sonic hedgehog (SHH) and group 3 (G3) MB samples from six patients. For each patient specimen, we developed two sPDX and iPDX models, respectively. Three Patch+/- GEMM models were also included for sequencing. Single-cell RNA sequencing was performed to compare gene expression profiles, cellular composition, and functional pathway enrichment. Bulk RNA-seq deconvolution was performed to compare cellular composition across models and human samples. RESULTS: Our results showed that the sPDX tumor model demonstrated the highest correlation to the overall transcriptomic profiles of primary human tumors at the single-cell level within the SHH and G3 subgroups, followed by the GEMM model and iPDX. The GEMM tumor model was able to recapitulate all subpopulations of tumor microenvironment (TME) cells that can be clustered in human SHH tumors, including a higher proportion of tumor-associated astrocytes and immune cells, and an additional cluster of vascular endothelia when compared to human SHH tumors. CONCLUSIONS: This study was the first to compare experimental models for MB at the single-cell level, providing value insights into model selection for different research purposes. sPDX and iPDX are suitable for drug testing and personalized therapy screenings, whereas GEMM models are valuable for investigating the interaction between tumor and TME cells.

Deubiquitylase ubiquitin-specific protease 7 plays a crucial role in the lineage differentiation of preimplantation blastocysts†.

Preimplantation embryos undergo a series of important biological events, including epigenetic reprogramming and lineage differentiation, and the key genes and specific mechanisms that regulate these events are critical to reproductive success. Ubiquitin-specific protease 7 (USP7) is a deubiquitinase involved in the regulation of a variety of cellular functions, yet its precise function and mechanism in preimplantation embryonic development remain unknown. Our results showed that RNAi-mediated silencing of USP7 in mouse embryos or treatment with P5091, a small molecule inhibitor of USP7, significantly reduced blastocyst rate and blastocyst quality, and decreased total and trophectoderm cell numbers per blastocyst, as well as destroyed normal lineage differentiation. The results of single-cell RNA-seq, reverse transcription-quantitative polymerase chain reaction, western blot, and immunofluorescence staining indicated that interference with USP7 caused failure of the morula-to-blastocyst transition and was accompanied by abnormal expression of key genes (Cdx2, Oct4, Nanog, Sox2) for lineage differentiation, decreased transcript levels, increased global DNA methylation, elevated repressive histone marks (H3K27me3), and decreased active histone marks (H3K4me3 and H3K27ac). Notably, USP7 may regulate the transition from the morula to blastocyst by stabilizing the target protein YAP through the ubiquitin-proteasome pathway. In conclusion, our results suggest that USP7 may play a crucial role in preimplantation embryonic development by regulating lineage differentiation and key epigenetic modifications.

The association between the number of pregnancies and depressive symptoms: A population-based study.

BACKGROUND: Depression is a psychosomatic disorder that affects reproductive health. The number of pregnancies is an important indicator of reproductive health. Multiple pregnancies and births may aggravate the risk of depression in females. However, the evidence of the connection between the number of pregnancies and depression is unclear. We aimed to investigate the relationship between the number of pregnancies and depressive symptoms. METHODS: We used the National Health and Nutrition Examination Survey (NHANES) data with a total of 17,216 women from 2005 to 2020. The number of pregnancies obtained from the self-report questionnaire. Depressive symptoms were measured by the nine-item patient health questionnaire (PHQ-9). Multivariate logistic regression models were used to examine the risk factors of depression. The restricted cubic spline (RCS) was applied to explore the nonlinear relationship. In addition, subgroup analysis was used to support the accuracy of our findings. RESULTS: We found that the number of pregnancies is positively associated with the prevalence of depression. According to the multivariable logistic regression analysis, pregnant women was 1.52-fold higher than the normal group to experience depression in the fully-adjusted model. No interaction between number of pregnancies and covariates in subgroups. LIMITATIONS: This study was cross-sectional, which limits its ability to draw conclusions about the causal relationship between the number of pregnancies and depression. CONCLUSION: In the United States, the number of pregnancies was positively associated with the prevalence of depression. It is critical to register the number of pregnancies for monitoring depressive symptoms.

Relationship between systemic immune inflammation index and mortality among US adults with different diabetic status: Evidence from NHANES 1999-2018.

OBJECTIVE: To investigate the association between systemic immune inflammation index (SII) and all-cause or cardiovascular diseases (CVDs) mortality in US adults with different diabetic status based on the National Health and Nutrition Examination Survey (NHANES) database. STUDY DESIGN AND SETTING: Adults with follow-up data in the NHANES 1999-2018 cycles were included in this study. The SII was calculated based on blood cells counts (including neutrophils, lymphocytes, and platelets) measured in the laboratory data. According to the quartiles of SII, population were divided into four groups (Q1-Q4). Mortality data was determined by linking NHANES survey participants to the National Death Index records, which collect mortality data and determine their vital status. Cox regression models were also performed to explore the hazard ratio (HR) and the corresponding 95 % confidence interval (95 % CI) of SII related with all-cause and CVDs mortality. In addition, restricted cubic spline was used to explore the nonlinear relationship between SII and mortality. Subgroup analysis and sensitivity analysis were performed to confirm the robustness of our results. RESULTS: In this study, there were 45,454 participants were enrolled (50.43 % females), with a mean age of 47.35 ± 0.19 years. Among of which, 7971 were diabetes patients and 3281 were pre-diabetes. With the mean 9.89 ± 0.08 follow-up years, there were 6935 (15.26 %) deaths occurred. Of which, 1795 deaths were caused by CVDs. The age-adjusted death rates were higher in participants with high SII levels compared to those with low SII levels. Cox regression analysis, after adjusting for covariates, revealed that SII levels were associated with an increased risk of all-cause mortality (HR, 1.02; 95 % CI, 1.02-1.03, P < 0.0001) and CVDs mortality (HR, 1.05; 95 % CI, 1.02-1.08, P = 0.002) in the fully adjusted Model. Moreover, there was a slight increase in HR values with the progression of diabetes status. Restricted cubic spline analysis demonstrated a "U-shaped" relationship between SII and all-cause mortality in diabetic, pre-diabetic and non-diabetic populations (all the P for nonlinear < 0.001). In addition, the relationship between SII and CVDs mortality was also nonlinear in both the pre-diabetic and non-diabetic populations (both P < 0.001). However, there was a linear relationship between SII and cardiovascular mortality in individuals with diabetes (P = 0.528). CONCLUSION: The SII is closely associated with the risk of all-cause and cardiovascular mortality. These associations vary among individuals with different diabetic states. Therefore, monitoring systemic inflammation and SII values is crucial in mitigating the risk of mortality.

Construction and validation of a progression prediction model for locally advanced rectal cancer patients received neoadjuvant chemoradiotherapy followed by total mesorectal excision based on machine learning.

Background: We attempted to develop a progression prediction model for local advanced rectal cancer(LARC) patients who received preoperative neoadjuvant chemoradiotherapy(NCRT) and operative treatment to identify high-risk patients in advance. Methods: Data from 272 LARC patients who received NCRT and total mesorectal excision(TME) from 2011 to 2018 at the Fourth Hospital of Hebei Medical University were collected. Data from 161 patients with rectal cancer (each sample with one target variable (progression) and 145 characteristic variables) were included. One Hot Encoding was applied to numerically represent some characteristics. The K-Nearest Neighbor (KNN) filling method was used to determine the missing values, and SmoteTomek comprehensive sampling was used to solve the data imbalance. Eventually, data from 135 patients with 45 characteristic clinical variables were obtained. Random forest, decision tree, support vector machine (SVM), and XGBoost were used to predict whether patients with rectal cancer will exhibit progression. LASSO regression was used to further filter the variables and narrow down the list of variables using a Venn diagram. Eventually, the prediction model was constructed by multivariate logistic regression, and the performance of the model was confirmed in the validation set. Results: Eventually, data from 135 patients including 45 clinical characteristic variables were included in the study. Data were randomly divided in an 8:2 ratio into a data set and a validation set, respectively. Area Under Curve (AUC) values of 0.72 for the decision tree, 0.97 for the random forest, 0.89 for SVM, and 0.94 for XGBoost were obtained from the data set. Similar results were obtained from the validation set. Twenty-three variables were obtained from LASSO regression, and eight variables were obtained by considering the intersection of the variables obtained using the previous four machine learning methods. Furthermore, a multivariate logistic regression model was constructed using the data set; the ROC indicated its good performance. The ROC curve also verified the good predictive performance in the validation set. Conclusions: We constructed a logistic regression model with good predictive performance, which allowed us to accurately predict whether patients who received NCRT and TME will exhibit disease progression.