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.

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.

Deubiquitylase USP7 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. 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 TE cell numbers per blastocyst, as well as destroying normal lineage differentiation. The results of single-cell RNA-seq, RT-qPCR, 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.

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.

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.

Fimepinostat Impairs NF-κB and PI3K/AKT Signaling and Enhances Gemcitabine Efficacy in H3.3K27M-Diffuse Intrinsic Pontine Glioma.

Diffuse intrinsic pontine glioma (DIPG) is the most aggressive pediatric brain tumor, and the oncohistone H3.3K27M mutation is associated with significantly worse clinical outcomes. Despite extensive research efforts, effective approaches for treating DIPG are lacking. Through drug screening, we identified the combination of gemcitabine and fimepinostat as a potent therapeutic intervention for H3.3K27M DIPG. H3.3K27M facilitated gemcitabine-induced apoptosis in DIPG, and gemcitabine stabilized and activated p53, including increasing chromatin accessibility for p53 at apoptosis-related loci. Gemcitabine simultaneously induced a prosurvival program in DIPG through activation of RELB-mediated NF-κB signaling. Specifically, gemcitabine induced the transcription of long terminal repeat elements, activated cGAS-STING signaling, and stimulated noncanonical NF-κB signaling. A drug screen in gemcitabine-treated DIPG cells revealed that fimepinostat, a dual inhibitor of HDAC and PI3K, effectively suppressed the gemcitabine-induced NF-κB signaling in addition to blocking PI3K/AKT activation. Combination therapy comprising gemcitabine and fimepinostat elicited synergistic antitumor effects in vitro and in orthotopic H3.3K27M DIPG xenograft models. Collectively, p53 activation using gemcitabine and suppression of RELB-mediated NF-κB activation and PI3K/AKT signaling using fimepinostat is a potential therapeutic strategy for treating H3.3K27M DIPG. SIGNIFICANCE: Gemcitabine activates p53 and induces apoptosis to elicit antitumor effects in H3.3K27M DIPG, which can be enhanced by blocking NF-κB and PI3K/AKT signaling with fimepinostat, providing a synergistic combination therapy for DIPG.

Inhibition of USP21 leads to ovarian carcinoma cell death by suppressing MAPK signaling.

Ovarian cancer is the most aggressive and lethal of all gynecologic malignancies. Although the overexpression (OE) of ubiquitin-specific peptidase 21 (USP21) has been observed in multiple cancers, its expression profile and biological function in ovarian cancer remain unknown. The expression levels of USP21 in ovarian cancer cells and tissues as well as adjacent normal tissues were assessed by qRT-PCR or Western blot assay. The biological function of USP21 in ovarian cancer cells was assessed by cell growth assay in vitro and a tumor growth model in vivo. Our study revealed that USP21 was markedly elevated in ovarian carcinoma tissues compared with adjacent normal tissues. Downregulation of USP21 attenuated the expression levels of MEK2 and p-ERK1/2. Depletion of USP21 resulted in suppressed cell growth of ovarian cancers in vitro and inhibited tumor growth in vivo. Conversely, OE of USP21 promoted the cell proliferation of ovarian cancers and conferred resistance to BAY 11-7082. These findings provide evidences supporting the notion of USP21 as a promising therapeutic target for the treatment of ovarian cancer.

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.

Optimal weak measurement scheme for chiral molecular detection based on photonic spin Hall effect.

In this paper, we propose a precision method to measure the chiroptical signal of Artemisinin solutions using the photonic spin Hall effect (PSHE) on the Ce:YIG-YIG-SiO2 structure as a probe. The effects of transmission distance, incident angles, applied magnetic fields of different directions, and beam waist of light on the weak measurement system are analytically investigated through simulations. It is found that decreasing the beam waist of the incident spot, increasing the incident angle, increasing the transmission distance, and adding a longitudinal magnetic field is conducive to enhancing the amplification transverse shift of PSHE, thus the measurement sensitivity is greatly improved. Based on the optimal weak measurement scheme, the detection limit for concentration measurement of artemisinin based on optical rotatory (OR) was reduced to 0.05 mg/ml. The measurement precision of the OR angle has been improved to 10-7rad.

Graph Reinforcement Learning-Based Decision-Making Technology for Connected and Autonomous Vehicles: Framework, Review, and Future Trends.

The proper functioning of connected and autonomous vehicles (CAVs) is crucial for the safety and efficiency of future intelligent transport systems. Meanwhile, transitioning to fully autonomous driving requires a long period of mixed autonomy traffic, including both CAVs and human-driven vehicles. Thus, collaborative decision-making technology for CAVs is essential to generate appropriate driving behaviors to enhance the safety and efficiency of mixed autonomy traffic. In recent years, deep reinforcement learning (DRL) methods have become an efficient way in solving decision-making problems. However, with the development of computing technology, graph reinforcement learning (GRL) methods have gradually demonstrated the large potential to further improve the decision-making performance of CAVs, especially in the area of accurately representing the mutual effects of vehicles and modeling dynamic traffic environments. To facilitate the development of GRL-based methods for autonomous driving, this paper proposes a review of GRL-based methods for the decision-making technologies of CAVs. Firstly, a generic GRL framework is proposed in the beginning to gain an overall understanding of the decision-making technology. Then, the GRL-based decision-making technologies are reviewed from the perspective of the construction methods of mixed autonomy traffic, methods for graph representation of the driving environment, and related works about graph neural networks (GNN) and DRL in the field of decision-making for autonomous driving. Moreover, validation methods are summarized to provide an efficient way to verify the performance of decision-making methods. Finally, challenges and future research directions of GRL-based decision-making methods are summarized.

Trust game, survey trust, are they correlated? Evidence from China.

Trust Game and survey trust are the two most popular measurements in the field of trust research, but most studies conducted in developing countries have found low or even insignificant correlations between them, we therefore validated this phenomenon in the cultural context of the largest developing country, China. Within-country differences can be of the same magnitude as the between country differences, especially in a culturally diverse China. Thus, we focus on comparing the characteristics of trust in the South and North regions of China. Through zero-order correlation and hierarchical regression analysis, our findings are consistent with those of numerous developing countries: Trust Game is lowly correlated with in-group trust survey and not with out-group trust survey. On the other hand, we found that Chinese individuals exhibit a distinct pattern of in-group trust, and there is no fundamental difference in the characteristics of trust between the South and the North.

Zinc supplementation promotes oocyte maturation and subsequent embryonic development in sheep.

Zinc plays a crucial role in the growth and reproductive functions of animals. Despite the positive effects of zinc that have been reported in oocytes of cows, pigs, yaks, and other animals, the influence of zinc on sheep is little known. To investigate the effect of zinc on the in vitro maturation of sheep oocytes and subsequent parthenogenesis-activated embryonic development, we added different concentrations of zinc sulfate to the in vitro maturation (IVM) culture medium. The IVM culture medium with zinc improved the maturation of sheep oocytes and the subsequent blastocyst rate after parthenogenesis activation. Notably, it also enhanced the level of glutathione and mitochondrial activity while reducing levels of reactive oxygen species. Thus, zinc addition to the IVM medium improved the quality of oocytes with a positive effect on the subsequent development of oocytes and embryos.

Amelioration of cadmium cytotoxicity to human cells by nutrient cation contents and the building of a biotic ligand model.

A variety of important major and trace elements may competitively inhibit cadmium (Cd) absorption in human cells and reduce Cd toxicity. However, the impact of essential elements on the cytotoxicity of metals can be difficult to quantify and anticipate. Cd acute toxicity to Caco-2 cell viability was studied in culture solutions and modeled by a biotic ligand model (BLM). The individual effects of the cations potassium (K+), calcium (Ca2+), magnesium (Mg2+), ferrous ion(Fe2+), zinc (Zn2+) and manganese (Mn2+) on Cd toxicity were also investigated. The results indicated that the toxicity of Cd in culture solutions to cell viability declined with increasing concentrations of Zn2+ and Mn2+ in the solutions, while K+, Ca2 +, Mg2 + and Fe2+ had no significant effect. Using the BLM, the stability constants for the binding of Cd2 +, Zn2+, and Mn2+ to biotic ligands were determined to be logKCdBL = 5.76, logKZnBL = 4.39 and logKMnBL = 5.31, respectively. Moreover, it was calculated that 51% occupancy of the biotic ligand sites for Cd by Cd was required to cause a 50% reduction in Caco-2 cell viability. A BLM was successfully established using the estimated constants to predict the Cd cytotoxicity to Caco-2 cell viability as a function of solution characteristics, so that the effective concentrations that reduced cell viability by 50% (EC50) could be predicted by the BLM within 1.6 fold changes of the observed EC50. The application's viability and precision for foretelling Cd toxicity in Caco-2 cells are discussed.

IFN-beta and EIF2AK2 are potential biomarkers for interstitial lung disease in anti-MDA5 positive dermatomyositis.

OBJECTIVE: DM with positive anti-melanoma differentiation-related gene 5 (MDA5) antibody is an autoimmune disease with multiple complications. Interstitial lung diseases (ILDs) are significantly associated with DM and are particularly related to MDA5+ DM. This article aims to explore potential molecular mechanisms and develop new diagnostic biomarkers for MDA5+ DM-ILD. METHODS: The series matrix files of DM and non-specific interstitial pneumonia (NSIP) were downloaded from the Gene Expression Omnibus (GEO) database to identify the differentially expressed genes (DEGs). Gene set enrichment analysis (GSEA) was used to screen the common enriched pathways related to DM and NSIP. Next, the co-expressed differential expressed genes (co-DEGs) between MDA5+, MDA5- and NSIP groups were identified by Venn plots, and then selected for different enrichment analyses and protein-protein interaction (PPI) network construction. The mRNA expression levels of IFN-beta and EIF2AK2 were measured by RT-qPCR. The protein expression levels of IFN-beta were measured by ELISA. RESULTS: Using GSEA, the enriched pathway 'herpes simplex virus 1 infection' was both up-regulated in DM and NSIP. Enrichment analysis in MDA5+ DM, MDA5- DM and NSIP reported that the IFN-beta signalling pathway was an important influencing factor in the MDA5+ DM-ILD. We also identified that eukaryotic translation initiation factor 2 alpha kinase 2 (EIF2AK2) was an important gene signature in the MDA5+ DM-ILD by PPI analysis. The expression levels of IFN-beta and EIF2AK2 were significantly increased in MDA5+ DM-ILD patients. CONCLUSIONS: IFN-beta and EIF2AK2 contributed to the pathogenesis of MDA5+ DM-ILD, which could be used as potential therapeutic targets.

Inflammasomes cross-talk with lymphocytes to connect the innate and adaptive immune response.

BACKGROUND: Innate and adaptive immunity are two different parts of the immune system that have different characteristics and work together to provide immune protection. Inflammasomes are a major part of the innate immune system that are expressed widely in myeloid cells and are responsible for inflammatory responses. Recent studies have shown that inflammasomes are also expressed and activated in lymphocytes, especially in T and B cells, to regulate the adaptive immune response. Activation of inflammasomes is also under the control of lymphocytes. Therefore, we propose that inflammasomes act as a bridge and they provide crosstalk between the innate and adaptive immune systems to obtain a fine balance in immune responses. AIM OF REVIEW: This review systematially summarizes the interaction between inflammasomes and lymphocytes and describes the crosstalk between the innate and adaptive immune systems induced by inflammasomes, with the aim of providing new directions and important areas for further research. KEY SCIENTIFIC CONCEPTS OF REVIEW: When considering the novel function of inflammasomes in various lymphocytes, attention should be given to the activity of specific inflammasomes in studies of lymphocyte function. Moreover, research on the function of various inflammasomes in lymphocytes will help advance knowledge on the mechanisms and treatment of various diseases, including autoimmune diseases and tumors. In addition, when studying inflammatory responses, inflammasomes in both lymphocytes and myeloid cells need to be considered.

Therapeutic targeting the oncogenic driver EWSR1::FLI1 in Ewing sarcoma through inhibition of the FACT complex.

EWS/ETS fusion transcription factors, most commonly EWSR1::FLI1, drives initiation and progression of Ewing sarcoma (EwS). Even though direct targeting EWSR1::FLI1 is a formidable challenge, epigenetic/transcriptional modulators have been proved to be promising therapeutic targets for indirectly disrupting its expression and/or function. Here, we identified structure-specific recognition protein 1 (SSRP1), a subunit of the Facilitates Chromatin Transcription (FACT) complex, to be an essential tumor-dependent gene directly induced by EWSR1::FLI1 in EwS. The FACT-targeted drug CBL0137 exhibits potent therapeutic efficacy against multiple EwS preclinical models both in vitro and in vivo. Mechanistically, SSRP1 and EWSR1::FLI1 form oncogenic positive feedback loop via mutual transcriptional regulation and activation, and cooperatively promote cell cycle/DNA replication process and IGF1R-PI3K-AKT-mTOR pathway to drive EwS oncogenesis. The FACT inhibitor drug CBL0137 effectively targets the EWSR1::FLI1-FACT circuit, resulting in transcriptional disruption of EWSR1::FLI1, SSRP1 and their downstream effector oncogenic signatures. Our study illustrates a crucial role of the FACT complex in facilitating the expression and function of EWSR1::FLI1 and demonstrates FACT inhibition as a novel and effective epigenetic/transcriptional-targeted therapeutic strategy against EwS, providing preclinical support for adding EwS to CBL0137's future clinical trials.

Quantitative ion character-activity relationship methods for assessing the ecotoxicity of soil metal(loid)s to lettuce.

New pollution elements introduced by the rapid development of modern industry and agriculture may pose a serious threat to the soil ecosystem. To explore the ecotoxicity and risk of these elements, we systematically studied the acute toxicity of 18 metal(loid)s toward lettuce using hydroponic experiments and quantitative relationships between element toxicity and ionic characteristics using ion-grouping and ligand-binding theory methods, thereby establishing a quantitative ion character-activity relationship (QICAR) model for predicting the phytotoxicity threshold of data-poor elements. The toxicity of 18 ions to lettuce differed by more than four orders of magnitude (0.05-804.44 µM). Correlation and linear regression analysis showed that the ionic characteristics significantly associated with this toxicity explained only 23.8-50.3% of the toxicity variation (R2Adj = 0.238-0.503, p < 0.05). Relationships between toxicity and ionic properties significantly improved after separating metal(loid) ions into soft and hard, with R2Adj of 0.793 and 0.784 (p < 0.05), respectively. Three ligand-binding parameters showed different predictive effects on lettuce metal(loid) toxicity. Compared with the binding constant of the biotic ligand model (log K) and the hard ligand scale (HLScale) (p > 0.05), the softness consensus scale (σCon) was significantly correlated with toxicity and provided the best prediction (R2Adj = 0.844, p < 0.001). We selected QICAR equations based on soft-hard ion classification and σCon methods to predict phytotoxicity of metal(loid)s, which can be used to derive ecotoxicity for data-poor metal(loid)s, providing preliminary assessment of their ecological risks.

Single-cell transcriptomics uncovers cellular architecture and developmental trajectories in hepatoblastoma.

BACKGROUND AND AIMS: Hepatoblastoma (HB) is the predominant type of childhood liver cancer. Treatment options for the clinically advanced HB remain limited. We aimed to dissect the cellular and molecular basis underlying HB oncogenesis and heterogeneity at the single-cell level, which could facilitate a better understanding of HB at both the biological and clinical levels. APPROACH AND RESULTS: Single-cell transcriptome profiling of tumor and paired distal liver tissue samples from five patients with HB was performed. Deconvolution analysis was used for integrating the single-cell transcriptomic profiles with the bulk transcriptomes of our HB cohort of post-neoadjuvant chemotherapy tumor samples. A single-cell transcriptomic landscape of early human liver parenchymal development was established for exploring the cellular root and hierarchy of HB oncogenesis. As a result, seven distinct tumor cell subpopulations were annotated, and an effective HB subtyping method was established based on their compositions. A HB tumor cell hierarchy was further revealed to not only fit with the classical cancer stem cell (CSC) model but also mirror the early human liver parenchymal development. Moreover, FACT inhibition, which could disrupt the oncogenic positive feedback loop between MYC and SSRP1 in HB, was identified as a promising epigenetic-targeted therapeutic strategy against the CSC-like HB1-Pro-like1 subpopulation and its related high-risk "Pro-like1" subtype of HB. CONCLUSIONS: Our findings illustrate the cellular architecture and developmental trajectories of HB via integrative bulk and single-cell transcriptome analyses, thus establishing a resourceful framework for the development of targeted diagnostics and therapeutics in the future.

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.

SMAD9-MYCN positive feedback loop represents a unique dependency for MYCN-amplified neuroblastoma.

BACKGROUND: Neuroblastoma (NB) is the most common extracranial solid tumor occurring during childhood and high-risk NB patients have a poor prognosis. The amplified MYCN gene serves as an important determinant of a high risk of NB. METHODS: We performed an integrative screen using public NB tissue and cell line data, and identified that SMAD9 played an important role in high-risk NB. An investigation of the super-enhancers database (SEdb) and chromatin immunoprecipitation sequencing (ChIP-seq) dataset along with biological experiments of incorporating gene knockdown and CRISPR interference (CRISPRi) were performed to identify upstream regulatory mechanism of SMAD9. Gene knockdown and rescue, quantitative real-time PCR (Q-RT-PCR), cell titer Glo assays, colony formation assays, a subcutaneous xenograft model and immunohistochemistry were used to determine the functional role of SMAD9 in NB. An integrative analysis of ChIP-seq data with the validation of CRISPRi and dual-luciferase reporter assays and RNA sequencing (RNA-seq) data with Q-RT-PCR validation was conducted to analyze the downstream regulatory mechanism of SMAD9. RESULTS: High expression of SMAD9 was specifically induced by the transcription factors including MYCN, PHOX2B, GATA3 and HAND2 at the enhancer region. Genetic suppression of SMAD9 inhibited MYCN-amplified NB cell proliferation and tumorigenicity both in vitro and in vivo. Further studies revealed that SMAD9 bound to the MYCN promoter and transcriptionally regulate MYCN expression, with MYCN reciprocally binding to the SMAD9 enhancer and transactivating SMAD9, thus forming a positive feedback loop along with the MYCN-associated cancer cell cycle. CONCLUSION: This study delineates that SMAD9 forms a positive transcriptional feedback loop with MYCN and represents a unique tumor-dependency for MYCN-amplified neuroblastoma.