Prognostic significance of migrasomes in neuroblastoma through machine learning and multi-omics.

This study explores migrasomes' role in neuroblastoma, a common malignant tumor in children, and their potential impact on tumor formation. We analyzed neuroblastoma RNA-seq datasets from public databases, including GSE62564, GSE181559, target, and fwr144. Through data normalization and unsupervised classification using migrasome-specific molecular markers, Differentially Expressed Genes were identified, followed by functional enrichment analysis. Our novel migrasome-associated machine learning model, MigScore, was developed using ten algorithms and 101 combinations, validated on two single-cell datasets. This enabled immune infiltration assessment and drug compatibility prediction, highlighting the utility of MS275, a histone deacetylase inhibitor. Results showed a significant inverse relationship between MigScore and favorable clinical outcomes, elucidating the link between migrasome pathways and tumor immunogenicity. These findings suggest that migrasomes are crucial in neuroblastoma prognosis, leading to the possibility of personalized treatment strategies and improved outcomes.

A mitochondria-related genes associated neuroblastoma signature - based on bulk and single-cell transcriptome sequencing data analysis, and experimental validation.

Background: Neuroblastoma (NB), characterized by its marked heterogeneity, is the most common extracranial solid tumor in children. The status and functionality of mitochondria are crucial in regulating NB cell behavior. While the significance of mitochondria-related genes (MRGs) in NB is still missing in key knowledge. Materials and methods: This study leverages consensus clustering and machine learning algorithms to construct and validate an MRGs-related signature in NB. Single-cell data analysis and experimental validation were employed to characterize the pivotal role of FEN1 within NB cells. Results: MRGs facilitated the classification of NB patients into 2 distinct clusters with considerable differences. The constructed MRGs-related signature and its quantitative indicators, mtScore and mtRisk, effectively characterize the MRGs-related patient clusters. Notably, the MRGs-related signature outperformed MYCN in predicting NB patient prognosis and was adept at representing the tumor microenvironment (TME), tumor cell stemness, and sensitivity to the chemotherapeutic agents Cisplatin, Topotecan, and Irinotecan. FEN1, identified as the most contributory gene within the MRGs-related signature, was found to play a crucial role in the communication between NB cells and the TME, and in the developmental trajectory of NB cells. Experimental validations confirmed FEN1's significant influence on NB cell proliferation, apoptosis, cell cycle, and invasiveness. Conclusion: The MRGs-related signature developed in this study offers a novel predictive tool for assessing NB patient prognosis, immune infiltration, stemness, and chemotherapeutic sensitivity. Our findings unveil the critical function of FEN1 in NB, suggesting its potential as a therapeutic target.

Development and validation of a novel stemness-related prognostic model for neuroblastoma using integrated machine learning and bioinformatics analyses.

Background: Neuroblastoma (NB) is a common solid tumor in children, with a dismal prognosis in high-risk cases. Despite advancements in NB treatment, the clinical need for precise prognostic models remains critical, particularly to address the heterogeneity of cancer stemness which plays a pivotal role in tumor aggressiveness and patient outcomes. By utilizing machine learning (ML) techniques, we aimed to explore the cancer stemness features in NB and identify stemness-related hub genes for future investigation and potential targeted therapy. Methods: The public dataset GSE49710 was employed as the training set for acquire gene expression data and NB sample information, including age, stage, and MYCN amplification status and survival. The messenger RNA (mRNA) expression-based stemness index (mRNAsi) was calculated and patients were grouped according to their mRNAsi value. Stemness-related hub genes were identified from the differentially expressed genes (DEGs) to construct a gene signature. This was followed by evaluating the relationship between cancer stemness and the NB immune microenvironment, and the development of a predictive nomogram. We assessed the prognostic outcomes including overall survival (OS) and event-free survival, employing machine learning methods to measure predictive accuracy through concordance indices and validation in an independent cohort E-MTAB-8248. Results: Based on mRNAsi, we categorized NB patients into two groups to explore the association between varying levels of stemness and their clinical outcomes. High mRNAsi was linked to the advanced International Neuroblastoma Staging System (INSS) stage, amplified MYCN, and elder age. High mRNAsi patients had a significantly poorer prognosis than low mRNAsi cases. According to the multivariate Cox analysis, the mRNAsi was an independent risk factor of prognosis in NB patients. After least absolute shrinkage and selection operator (LASSO) regression analysis, four key genes (ERCC6L, DUXAP10, NCAN, DIRAS3) most related to mRNAsi scores were discovered and a risk model was built. Our model demonstrated a significant prognostic capacity with hazard ratios (HR) ranging from 18.96 to 41.20, P values below 0.0001, and area under the receiver operating characteristic curve (AUC) values of 0.918 in the training set, suggesting high predictive accuracy which was further confirmed by external verification. Individuals with a low four-gene signature score had a favorable outcome and better immune responses. Finally, a nomogram for clinical practice was constructed by integrating the four-gene signature and INSS stage. Conclusions: Our findings confirm the influence of CSC features in NB prognosis. The newly developed NB stemness-related four-gene signature prognostic signature could facilitate the prognostic prediction, and the identified hub genes may serve as promising targets for individualized treatments.

Optimal combination of MYCN differential gene and cellular senescence gene predicts adverse outcomes in patients with neuroblastoma.

Introduction: Neuroblastoma (NB) is a common extracranial tumor in children and is highly heterogeneous. The factors influencing the prognosis of NB are not simple. Methods: To investigate the effect of cell senescence on the prognosis of NB and tumor immune microenvironment, 498 samples of NB patients and 307 cellular senescence-related genes were used to construct a prediction signature. Results: A signature based on six optimal candidate genes (TP53, IL-7, PDGFRA, S100B, DLL3, and TP63) was successfully constructed and proved to have good prognostic ability. Through verification, the signature had more advantages than the gene expression level alone in evaluating prognosis was found. Further T cell phenotype analysis displayed that exhausted phenotype PD-1 and senescence-related phenotype CD244 were highly expressed in CD8+ T cell in MYCN-amplified group with higher risk-score. Conclusion: A signature constructed the six MYCN-amplified differential genes and aging-related genes can be used to predict the prognosis of NB better than using each high-risk gene individually and to evaluate immunosuppressed and aging tumor microenvironment.

Characterization and therapeutic perspectives of differentiation-inducing therapy in malignant tumors.

Cancer is a major public health issue globally and is one of the leading causes of death. Although available treatments improve the survival rate of some cases, many advanced tumors are insensitive to these treatments. Cancer cell differentiation reverts the malignant phenotype to its original state and may even induce differentiation into cell types found in other tissues. Leveraging differentiation-inducing therapy in high-grade tumor masses offers a less aggressive strategy to curb tumor progression and heightens chemotherapy sensitivity. Differentiation-inducing therapy has been demonstrated to be effective in a variety of tumor cells. For example, differentiation therapy has become the first choice for acute promyelocytic leukemia, with the cure rate of more than 90%. Although an appealing concept, the mechanism and clinical drugs used in differentiation therapy are still in their nascent stage, warranting further investigation. In this review, we examine the current differentiation-inducing therapeutic approach and discuss the clinical applications as well as the underlying biological basis of differentiation-inducing agents.

Autophagy Inhibition Contributes to Apoptosis of PLK4 Downregulation-induced Dormant Cells in Colorectal Cancer.

Dormant cancer cells account for cancer recurrence, distant metastasis and drug resistance which lead to poor prognosis in colorectal cancer (CRC). However, little is known about the molecular mechanisms regulating tumor cell dormancy and how to eliminate dormant cancer cells. Recent studies indicate autophagy affects dormant tumor cell survival. Here, we found that polo-like kinases 4 (PLK4), a central regulator of the cell cycle and proliferation, plays a crucial role in regulating CRC cells dormancy both in vitro and in vivo. Downregulation of PLK4 induced dormancy and inhibited migration and invasion in different CRC cell lines. Clinically, PLK4 expression was correlated with the dormancy markers (Ki67, p-ERK, p-p38) and late recurrence in CRC tissues. Mechanistically, downregulation of PLK4 induced autophagy contributed to restoring phenotypically aggressive tumor cells to a dormant state through the MAPK signaling pathway, and inhibition of autophagy would trigger apoptosis of dormant cells. Our findings reveal that downregulation of PLK4-induced autophagy contributes to tumor dormancy and autophagy inhibition leads to apoptosis of CRC dormant cells. Our study is the first to report that downregulation PLK4 induced autophagy is an early event in CRC dormancy and highlights autophagy inhibitor as a potential therapeutic target for dormant cell elimination.

Tumor dormancy is closely related to prognosis prediction and tumor immunity in neuroblastoma.

Background: Neuroblastoma (NB), which is the most frequent and fatal solid tumor in early childhood, lacks an accurate approach to prevent or forecast its recurrence. Dormant NB cells are responsible for metastasis, drug resistance, and suppressive activity in the immune system. However, there is a lack of systematic research on the interaction between dormancy and NB prognosis and its potential associations with tumor immunity. Methods: We downloaded NB gene expression data and clinical information from the Gene Expression Omnibus and ArrayExpres databases. Based on consensus clustering of the expression of dormancy-associated genes, the NB samples were classified into different groups, and differentially expressed genes (DEGs) were explored in each group. Functional analyses of DEGs were performed, followed by the establishment of a predictive dormancy signature and the assessment of tumor immunity. Finally, sex, age, International Neuroblastoma Staging System (INSS) stage, and MYCN status were identified as independent overall survival-related variables, which were incorporated into the nomogram. Results: A dormancy-associated gene signature, including CDKN2A, BHLHB3, CDKN2B, MAPK14, CDKN1B, and BMP7, was established. The gene signature showed a strong correlation with NB immune infiltration and capacity to predict NB patient prognosis. A nomogram including MYCN status, INSS stage, age and gene signature risk score was established which further divided NB into high, medium and low-risk groups. This nomogram had certain guiding significance in decision-making for clinical treatment. Conclusions: Our results suggested that the 6-gene genetic signature for NB based on dormancy could predict NB survival and response to immunotherapy.

Pyroptosis-Related Gene Signature Predicts the Prognosis and Immune Infiltration in Neuroblastoma.

Neuroblastoma is the most common pediatric extracranial solid tumor. The 5-year survival rate for high-risk neuroblastoma is less than 50%, despite multimodal treatment. Pyroptosis, an inflammatory type of programmed cell death, manifested pro-tumor and anti-tumor roles in the adult tumor. Thus, we aimed to elucidate the function of pyroptosis in neuroblastoma. We classified neuroblastoma patients into two clusters based on the pyroptosis gene expression. We found high pyroptosis neuroblastoma manifested favorable overall survival and more anti-tumor immune cell infiltration. Based on the results of a stepwise Cox regression analysis, we built a four-gene predictive model including NLRP3, CASP3, IL18, and GSDMB. The model showed excellent predictive performance in internal and external validation. Our findings highlight that high pyroptosis positively correlated with neuroblastoma outcomes and immune landscape, which may pave the way for further studies on inducing pyroptosis therapy in high-risk neuroblastoma treatment.

Single-Atom Metal Anchored Zr6-Cluster-Porphyrin Framework Hollow Nanocapsules with Ultrahigh Active-Center Density for Electrocatalytic CO2 Reduction.

Designing earth-abundant electrocatalysts toward highly efficient CO2 reduction has significant importance to decrease the global emission of greenhouse gas. Herein, we propose an efficient strategy to anchor non-noble metal single atoms on Zr6-cluster-porphyrin framework hollow nanocapsules with well-defined and abundant metal-N4 porphyrin sites for efficient electrochemical CO2 reduction. Among different transition metal single atoms (Mn, Fe, Co, Ni, and Cu), Co single-atom anchored Zr6-cluster-porphyrin framework hollow nanocapsules demonstrated the highest activity and selectivity for CO production. The rich Co-N4 active centers and hierarchical porous structure contribute to enhanced CO2 adsorption capability and moderate binding strength of reaction intermediates, thus facilitating *CO desorption and CO2-to-CO conversion. The Co-anchored nanocapsules maintain high efficiency and well-preserved stability during long-term electrocatalysis tests. Moreover, the Co-anchored nanocapsules exhibit a remarkable solar-to-CO energy conversion efficiency of 12.5% in an integrated solar-driven CO2 reduction/O2 evolution electrolysis system when powered by a custom large-area [Cs0.05(FA0.85MA0.15)0.95]Pb0.9(I0.85Br0.15)3-based perovskite solar cell.

2D Arsenene and Arsenic Materials: Fundamental Properties, Preparation, and Applications.

As emerging 2D materials, arsenene and arsenic materials have attracted rising interest in the past few years. The diverse crystalline phases, exotic electrical characteristics, and widespread applications of 2D arsenene and arsenic bring them great research value and utilization potential. Herein, the recent progress of 2D arsenene and arsenic is reviewed in terms of fundamental properties, preparation, and applications. The fundamental properties of 2D arsenene and arsenic, including the crystal phases, environmental stability, and electrical structure, from theoretical to experimental reports are first summarized. Then, the experimental processes for preparing 2D arsenene and arsenic, along with their respective advantages and disadvantages, are introduced including epitaxial growth, mechanical exfoliation, and liquid-phase exfoliation. Moreover, applications of 2D arsenene and arsenic are discussed, suggesting a wide range of applications of 2D arsenene and arsenic in field-effect transistors, sensors, catalysts, biological applications, and so on. Finally, some perspectives about the challenges and opportunities of promising 2D arsenene and arsenic are provided. This review provides a helpful guidance and stimulates more focus on future explorations and developments of 2D arsenene and arsenic.

Identification of a Five-Gene Signature Derived From MYCN Amplification and Establishment of a Nomogram for Predicting the Prognosis of Neuroblastoma.

Background: Neuroblastoma (NB), the most common solid tumor in children, exhibits vastly different genomic abnormalities and clinical behaviors. While significant progress has been made on the research of relations between clinical manifestations and genetic abnormalities, it remains a major challenge to predict the prognosis of patients to facilitate personalized treatments. Materials and Methods: Six data sets of gene expression and related clinical data were downloaded from the Gene Expression Omnibus (GEO) database, ArrayExpress database, and Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. According to the presence or absence of MYCN amplification, patients were divided into two groups. Differentially expressed genes (DEGs) were identified between the two groups. Enrichment analyses of these DEGs were performed to dig further into the molecular mechanism of NB. Stepwise Cox regression analyses were used to establish a five-gene prognostic signature whose predictive performance was further evaluated by external validation. Multivariate Cox regression analyses were used to explore independent prognostic factors for NB. The relevance of immunity was evaluated by using algorithms, and a nomogram was constructed. Results: A five-gene signature comprising CPLX3, GDPD5, SPAG6, NXPH1, and AHI1 was established. The five-gene signature had good performance in predicting survival and was demonstrated to be superior to International Neuroblastoma Staging System (INSS) staging and the MYCN amplification status. Finally, a nomogram based on the five-gene signature was established, and its clinical efficacy was demonstrated. Conclusion: Collectively, our study developed a novel five-gene signature and successfully built a prognostic nomogram that accurately predicted survival in NB. The findings presented here could help to stratify patients into subgroups and determine the optimal individualized therapy.

Electric-Field-Induced Ion Migration Behavior in Methylammonium Lead Iodide Perovskite.

Ionic movement inside organometal halide perovskites (OMHP) materials has been widely reported to be linked with stability issues in the perovskite-based optoelectronic devices. However, the dynamic processes of the ionic movement and how they influence the devices are still not well-understood. In this work, we applied an external electric field to the CH3NH3PbI3 crystal and simultaneously monitored the PL behaviors. Two successive PL responses were observed in the same location of the crystal. First, an irreversible PL quenching was observed caused by the photo-annealing effect under an electric field accompanied by a permanent morphology change. The annealed area also showed reversible PL variation, which was attributed to the activation-deactivation of the radiative recombination centers induced by the migration of the iodine ions. Such results can help us gain a deep insight into how the ionic movements in OMHPs influence the performance of the perovskite-based optoelectronic devices under working conditions.

Inhibition of Phase Segregation in Cesium Lead Mixed-Halide Perovskites by B-Site Doping.

The emergence of all-inorganic halide perovskites has shown great potential in photovoltaic and optoelectronic devices. However, the photo-induced phase segregation in lead mixed-halide perovskites has severely limited their application. Herein, by real-time monitoring the photoluminescence (PL) spectra of metal mixed-halide perovskites under light irradiation, we found that the photo-induced phase transition can be significantly inhibited by B-site doping. For pristine mixed-halide perovskites, an intermediate phase of CsPbBrxI3-x can only be stabilized under low excitation power. After introducing Sn2+ ions, such intermediate phase can be stabilized in nitrogen atmosphere under high excitation power and phase segregation can be started after the exposure in oxygen due to oxidization of Sn2+. Replacing Sn2+ by Mn2+ can further improve the intermediate phase's tolerance to oxygen proving that B-site doping in perovskites structure by Sn2+ or Mn2+ could effectively minimize the light-induced phase segregation and promote them to serve as promising candidates in photovoltaic and light-emitting devices.

Periostin mediates epithelial-mesenchymal transition through the MAPK/ERK pathway in hepatoblastoma.

OBJECTIVE: The aim of the present study was to analyze the prognostic factors in patients with hepatoblastoma (HB) in our single center and to evaluate periostin (POSTN) expression in HB and its association with clinicopathological variables. In addition, the underlying mechanism of how POSTN promotes HB progression was discussed. METHODS: POSTN expression was investigated in HB tumors by immunohistochemistry (IHC), immunofluorescence (IF) and Western blot (WB). The association among POSTN expression, clinicopathological features and overall survival (OS) was also evaluated. The migration and adhesion ability of HB cells were measured using chemotaxis and cell-matrix adhesion assays, respectively. Epithelial-mesenchymal transition (EMT)-associated markers and activation of the ERK pathway were detected by WB. RESULTS: HB patients had poor prognosis which displayed lymph node metastasis, vascular invasion, POSTN and vimentin expression. POSTN expression was also associated with lymph node metastasis. Furthermore, overexpressed POSTN promoted migration and the adhesive ability of HB cells in vitro. In addition, we demonstrated that POSTN activated the MAPK/ERK pathway, upregulated the expression of Snail and decreased the expression of OVOL2. Finally, POSTN promoted the expression of EMT-associated markers. CONCLUSIONS: POSTN might modulate EMT via the ERK signaling pathway, thereby promoting cellular migration and invasion. Our study also suggests that POSTN may serve as a therapeutic biomarker in HB patients.