The interplay between the tumor microenvironment and tumor-derived small extracellular vesicles in cancer development and therapeutic response.

The tumor microenvironment (TME) plays an essential role in tumor cell survival by profoundly influencing their proliferation, metastasis, immune evasion, and resistance to treatment. Extracellular vesicles (EVs) are small particles released by all cell types and often reflect the state of their parental cells and modulate other cells' functions through the various cargo they transport. Tumor-derived small EVs (TDSEVs) can transport specific proteins, nucleic acids and lipids tailored to propagate tumor signals and establish a favorable TME. Thus, the TME's biological characteristics can affect TDSEV heterogeneity, and this interplay can amplify tumor growth, dissemination, and resistance to therapy. This review discusses the interplay between TME and TDSEVs based on their biological characteristics and summarizes strategies for targeting cancer cells. Additionally, it reviews the current issues and challenges in this field to offer fresh insights into comprehending tumor development mechanisms and exploring innovative clinical applications.

Magnetically modified bacteriophage-triggered ATP release activated EXPAR-CRISPR/Cas14a system for visual detection of Burkholderia pseudomallei.

Burkholderia pseudomallei, widely distributed in tropical and subtropical ecosystems, is capable of causing the fatal zoonotic disease melioidosis and exhibiting a global trend of dissemination. Rapid and sensitive detection of B. pseudomallei is essential for environmental monitoring as well as infection control. Here, we developed an innovative biosensor for quantitatively detecting B. pseudomallei relies on ATP released triggered by bacteriophage-induced bacteria lysis. The lytic bacteriophage vB_BpP_HN01, with high specificity, is employed alongside magnetic nanoparticles assembly to create a biological receptor, facilitating the capture and enrichment of viable target bacteria. Following a brief extraction and incubation process, the captured target undergoes rapid lysis to release contents including ATP. The EXPAR-CRISPR cascade reaction provides an efficient signal transduction and dual amplification module that allowing the generated ATP to guide the signal output as an activator, ultimately converting the target bacterial amount into a detectable fluorescence signal. The proposed bacteriophage affinity strategy exhibited superior performance for B. pseudomallei detection with a dynamic range from 10^2 to 10^7 CFU mL-1, and a LOD of 45 CFU mL-1 within 80 min. Moreover, with the output signal compatible across various monitoring methods, this work offers a robust assurance for rapid diagnosis and on-site environmental monitoring of B. pseudomallei.

DNA-based molecular classifiers for the profiling of gene expression signatures.

Although gene expression signatures offer tremendous potential in diseases diagnostic and prognostic, but massive gene expression signatures caused challenges for experimental detection and computational analysis in clinical setting. Here, we introduce a universal DNA-based molecular classifier for profiling gene expression signatures and generating immediate diagnostic outcomes. The molecular classifier begins with feature transformation, a modular and programmable strategy was used to capture relative relationships of low-concentration RNAs and convert them to general coding inputs. Then, competitive inhibition of the DNA catalytic reaction enables strict weight assignment for different inputs according to their importance, followed by summation, annihilation and reporting to accurately implement the mathematical model of the classifier. We validated the entire workflow by utilizing miRNA expression levels for the diagnosis of hepatocellular carcinoma (HCC) in clinical samples with an accuracy 85.7%. The results demonstrate the molecular classifier provides a universal solution to explore the correlation between gene expression patterns and disease diagnostics, monitoring, and prognosis, and supports personalized healthcare in primary care.

​Meta-analysis of the applied value of the growth differentiation factor 15 detection in HFpEF diagnosis.

OBJECTIVE: To systematically evaluate the diagnostic value of growth differentiation factor-15 (GDF-15) for heart failure with preserved ejection fraction (HFpEF). METHODS: Chinese and English literature on the diagnosis of HFpEF using GDF-15 were searched in PubMed, Embase, Web of Science (WOS), Cochrane Library, China National Knowledge Infrastructure (CNKI), China Science and Technology Journal Database, WanFang Database, and others. The literature on the diagnostic value of the GDF-15 test for HFpEF was screened from the establishment of the database to April 2023 according to the inclusion and exclusion criteria. The quality of the included studies was then assessed based on the QUADAS-2 list, and the threshold effect was evaluated using the Meta-Disc1.4 software. STATA 17.0 software was used to combine the sensitivity, specificity, and area under the curve (AUC) of the included studies. Moreover, heterogeneity was evaluated by the inconsistency index (I2) and Cochrane Q index, and the source of heterogeneity was explored by subgroup analysis, meta-regression, and sensitivity analysis. Finally, Deek's quantitative funnel plot was used to assess whether there was publication bias among the included studies. RESULTS: A total of ten studies involving 1550 patients were included. The pooled sensitivity was 0.77 (95%CI: 0.70-0.83), the specificity was 0.79 (95%CI: 0.68-0.87), the positive likelihood ratio was 3.9 (95%CI: 2.6-5.9), and the negative likelihood ratio was 0.21 (95%CI:0.12-0.36). The diagnostic odds ratio was 19 (95%CI: 9-37), and the AUC of SROC was 0.88 (95%CI: 0.85-0.9). The results of the heterogeneity test showed significant heterogeneity among the studies (I2 = 96%, p = 0.000 < 0.01). Meta-regression analysis showed that there was a significant difference in diagnostic efficacy between the gold standard group (p = 0.0064 < 0.05), while there was no significant difference in diagnostic efficacy among the three subgroups of age, gender, and comprehensive group (p > 0.05). After excluding the articles that did not include biomarkers for the diagnosis of HFpEF, the average age ≥73 years old, and the proportion of women >55%, the remaining four articles had the pooled sensitivity of 0.80 (I2 = 60.1%, p = 0.06 >​ 0.05) and the pooled specificity of 0.84 (I2 = 0%, p = 0.61 >​0.05), which insisted that there is no significant heterogeneity among them. CONCLUSION: With its high sensitivity and specificity for HFpEF diagnosis, GDF-15 is a novel biomarker for HFpEF diagnosis.

RART-LAMP: One-Step Extraction-Free Method for Genotyping within 40 min.

Loop-mediated isothermal amplification (LAMP) is a commonly used alternative to PCR for point-of-care detection of nucleic acids due to its rapidity, sensitivity, specificity, and simpler instrumentation. While dual-labeled TaqMan probes are widely used in PCR for single-nucleotide polymorphism (SNP) genotyping, real-time LAMP primarily relies on turbidimetry or intercalator fluorescence measurements, which can be non-specific and generate false-positive results. In this study, we propose a closed-tube, dual-labeled RNA-modified probes and RNase H II-assisted real-time LAMP (RART-LAMP) method for SNP genotyping. Our findings indicate that (1) fluorescence signals were predominantly derived from probe hydrolysis rather than hybridization, (2) temperature-controlled hybridization between the probe and template ensured the specificity of SNP analysis, and (3) RNase H II hydrolysis between the target containing SNP sites and probes did not exhibit sequence specificity. Our RART-LAMP approach demonstrated excellent performance in genotyping C677T clinical samples, including gDNA extracted from blood, saliva, and swabs. More importantly, saliva and swab samples could be directly analyzed without any pretreatment, indicating promising prospects for nucleic acid analysis at the point of care in resource-limited settings.

A hairpin probe-mediated exponential amplification reaction for highly sensitive and specific detection of microRNAs.

In this work, we propose a hairpin probe-mediated exponential amplification reaction (HEAR) strategy that combines DNA strand displacement with a "who triggers, who gets generated" mode, providing excellent single-base discrimination and a reduced background signal. The detection limit is 19 aM, which is reduced by 3 orders of magnitude compared to traditional exponential amplification approaches. This one-pot strategy also exhibits a wide dynamic range, high specificity and short detection time. It is expected to become a powerful tool for clinical diagnosis.

A PAM-free CRISPR/Cas12a ultra-specific activation mode based on toehold-mediated strand displacement and branch migration.

CRISPR (clustered regularly interspaced short palindromic repeats) technology has achieved great breakthroughs in terms of convenience and sensitivity; it is becoming the most promising molecular tool. However, only two CRISPR activation modes (single and double stranded) are available, and they have specificity and universality bottlenecks that limit the application of CRISPR technology in high-precision molecular recognition. Herein, we proposed a novel CRISPR/Cas12a unrestricted activation mode to greatly improve its performance. The new mode totally eliminates the need for a protospacer adjacent motif and accurately activates Cas12a through toehold-mediated strand displacement and branch migration, which is highly universal and ultra-specific. With this mode, we discriminated all mismatch types and detected the EGFR T790M and L858R mutations in very low abundance. Taken together, our activation mode is deeply incorporated with DNA nanotechnology and extensively broadens the application boundaries of CRISPR technology in biomedical and molecular reaction networks.

Blocker displacement amplification mediated PCR based screen-printed carbon electrode biosensor and lateral flow strip strategy for CYP2C19*2 genotyping.

Single nucleotide variants in CYP2C19*2 are associated with clopidogrel resistance in coronary heart disease. In order the guidance the dosage of drug and personalized medicine, blocker displacement amplification was first used to specific amplify G site and A site alleles. For electrochemical strategy, forward primers were labeled electrochemical active methyl blue and ferrocene, generates signals on -0.26 for G site and 0.22 V for A site. For lateral flow strip assay, primers with specific modification were used to generates unique color in test line 1 for G site and test line 2 for A site. In conclusion, we developed a sensitive screen-printed carbon electrodes based electrochemical sensor and gold nano particle based lateral flow strip assay strategy to successfully genotyping CYP2C19*2 GG, GA and AA genotype. The proposed method can realize CYP2C19*2 analysis from multiple biological samples including whole blood, buccal swab, saliva and hair root, and showed good consistency with Sequencing. Due to the fact our proposed strategy merely relies on thermal cycler instrument and visual strip detection, this platform shows great potential in source-limited regions genotyping.

Specific and robust hybridization based on double-stranded nucleic acids with single-base resolution.

Nucleic acid hybridization plays a critical role in medical diagnostics and nanotechnology, but its selectivity and robustness remain to be improved. Here, focusing on double-stranded nucleic acid-based hybridization, we present a series of related strategies. Above all, two simple strategies for enriching toehold-included double-stranded nucleic acids have been proposed. On this basis, two universal hybridization methods with higher selectivity than typical toehold exchange reaction and a long target detection method using short probes to extend the detectable length range are realized. We also provide a double-stranded nucleic acids-catalyzed cycle amplification reaction to improve sensitivity, which has superior interference resistance and excellent discrimination for single-base mismatches. Besides, double-stranded nucleic acids with forked toeholds are used as essential elements to construct a series of logic gates that can evaluate different input combinations. Given the unique advantages of double-stranded nucleic acids, we expect the current work to advance the application of double-stranded nucleic acid-based hybridization in medical diagnostics and nanotechnology.

Ethanol promoting the upregulation of C-X-C Motif Chemokine Ligand 1（CXCL1） and C-X-C Motif Chemokine Ligand 6（CXCL6） in models of early alcoholic liver disease.

Alcoholic liver disease (ALD) denotes a series of liver diseases caused by ethanol. Recently, immune-related genes (IRGs) play increasingly crucial role in diseases. However, it's unclear the role of IRGs in ALD. Bioinformatic analysis was used to discern the core immune-related differential genes (IRDGs) in the present study. Subsequently, Cell Counting Kit-8 say, oil red O staining, and triglyceride detection were employed to explore optimal experimental conditions of establishing hepatocellular models of early ALD. Ultimately, real-time reverse transcription-PCR and immunohistochemistry/immunocytochemistry methods were adopted to verify the expressions of mRNA and proteins of core IRDGs, respectively. C-X-C Motif Chemokine Ligand 1 (Cxcl1) and Cxcl6 were regarded as core IRDGs via integrated bioinformatics analysis. Besides, Lieber Decarli Ethanol feeding and 200 mM and 300 mM ethanol stimulating L02 cells for 36 h can both successfully hepatocellular model. In ethanol groups, the levels of CXCL1 and CXCL6 mRNA were significantly upregulated than pair-fed groups (P < 0.0001). Also, immunohistochemistry revealed that positive particles of CXCL1 and CXCL6 in mice model of early ALD were obviously more than control groups (P < 0.0001). Besides, in L02 hepatocytes stimulated by ethanol, CXCL1 and CXCL6 mRNA were over-expressed, compared with normal L02 cells (P < 0.0001). Meanwhile, immunocytochemistry indicated that CXCL1 and CXCL6 proteins in hepatocellular model of early ALD were higher than normal L02 hepatocytes stimulus (P < 0.0001). Ethanol promoted the upregulation of Cxcl1 and Cxcl6 mRNA and proteins in models of early ALD, denoting their potentiality of acting as biomarkers of ALD.

Cooperative Branch Migration: A Mechanism for Flexible Control of DNA Strand Displacement.

DNA strand displacement plays an essential role in the field of dynamic DNA nanotechnology. However, flexible regulation of strand displacement remains a significant challenge. Most previous regulatory tools focused on controllable activation of toehold and thus limited the design flexibility. Here, we introduce a regulatory tool termed cooperative branch migration (CBM), through which DNA strand displacement can be controlled by regulating the complementarity of branch migration domains. CBM shows perfect compatibility with the majority of existing regulatory tools, and when combined with forked toehold, it permits continuous fine-tuning of the strand displacement rate spanning 5 orders of magnitude. CBM manifests multifunctional regulation ability, including rate fine-tuning, continuous dynamic regulation, reaction resetting, and selective activation. To exemplify the powerful function, we also constructed a nested if-function signal processing system on the basis of cascading CBM reactions. We believe that the proposed regulatory strategy would effectively enrich the DNA strand displacement toolbox and ultimately promote the construction of DNA machines of higher complexity in nucleic acid research and biomedical applications.

Integrated Analyses Identify Key Molecules and Reveal the Potential Mechanism of miR-182-5p/FOXO1 Axis in Alcoholic Liver Disease.

Background: Alcoholic liver disease (ALD) is one of the most common chronic liver diseases worldwide. However, the potential molecular mechanism in ALD development remains unclear. The objective of this work was to identify key molecules and demonstrate the underlying regulatory mechanisms. Methods: RNA-seq datasets were obtained from Gene Expression Omnibus (GEO), and key molecules in ALD development were identified with bioinformatics analysis. Alcoholic liver disease mouse and cell models were constructed using Lieber-DeCarli diets and alcohol medium, respectively. Quantitative real-time PCR and Western blotting were conducted to confirm the differential expression level. Dual-luciferase reporter assays were performed to explore the targeting regulatory relationship. Overexpression and knockdown experiments were applied to reveal the potential molecular mechanism in ALD development. Results: Between ALD patients and healthy controls, a total of 416 genes and 21 microRNAs (miRNAs) with significantly differential expression were screened. A comprehensive miRNA-mRNA network was established; within this network, the miR-182-5p/FOXO1 axis was considered a significant pathway in ALD lipid metabolism. Mouse and cell experiments validated that miR-182-5p was substantially higher in ALD than in normal livers, whereas the expression of FOXO1 was dramatically decreased by alcohol consumption (P < 0.05). Next, dual-luciferase reporter assays demonstrated that miR-182-5p directly targets the binding site of the FOXO1 3'UTR and inhibits its mRNA and protein expression. In addition, miR-182-5p was found to promote hepatic lipid accumulation via targeting the FOXO1 signaling pathway, and inhibition of the miR-182-5p/FOXO1 axis improved hepatic triglyceride (TG) deposition in ALD by regulating downstream genes involved in lipid metabolism. Conclusion: In summary, key molecules were identified in ALD development and a comprehensive miRNA-mRNA network was established. Meanwhile, our results suggested that miR-182-5p significantly increases lipid accumulation in ALD by targeting FOXO1, thereby providing novel scientific insights and potential therapeutic targets for ALD.

DNAzyme based three-way junction assay for antibody-free detection of locus-specific N6-methyladenosine modifications.

N6-methyladenosine (m6A) is the most abundant post-transcriptional modification in RNA and has important implications in physiological processes and tumor development. However, sensitive and specific quantification of locus-specific m6A modification levels remains a challenging task. In the present work, a novel m6A-sensitive DNAzyme was utilized to directly detect m6A by coupling with a three-way junction-mediated isothermal exponential CRISPR amplification reaction for the first time. This method was built on the fact that the binding arm of the DNAzyme bound to the specific site and its core structure catalyzed the selective cleavage of unmodified adenine instead of methylated adenines. Subsequently, the intact RNA was identified by the proximity effect of the three-way junction. Enormous amounts of single-stranded DNA products were generated through a combination of SDA and EXPAR for signal amplification. The specific real-time curve of products was recorded through detecting the fluorescence intensity triggered by CRISPR Cas12a. As a result, methylation target of abundance down to 1% was successfully identified. In addition, this strategy could be used for the analysis of cell RNA extracts. Combined with an electrochemical sensor for quantitative detection of RNA methylation, we demonstrated the generality of as-proposed strategy. We envision the present method would provide a new platform for the analysis of m6A in RNA and promote its application in clinical diseases.

A comprehensive system for detecting rare single nucleotide variants based on competitive DNA probe and duplex-specific nuclease.

Single nucleotide variants (SNVs) have emerged as increasingly important biomarkers, particularly in the diagnosis and prognosis of cancers. However, most SNVs are rarely detected in blood samples from cancer patients as they are surrounded by abundant concomitant wild-type nucleic acids. Herein, we design a system that features a combination of competitive DNA probe system (CDPS) and duplex-specific nuclease (DSN) that we referred to as CAD. A theoretical model was established for the CAD system based on reaction networks. Guided by the theoretical model, we found that a minor loss in sensitivity significantly improved the specificity of the system, thus creating a theoretical discrimination factor (DF) > 100 for most conditions. This non-equivalent tradeoff between sensitivity and specificity provides a new concept for the analysis of rare DNA-sequence variants. As a demonstration of practicality, we applied as-proposed CAD system to identify low variant allele frequency (VAF) in a synthetic template (0.1% VAF) and human genomic DNA (1% VAF). This work promises complete guidance for the design of enzyme-based nucleic acid analysis.

Exploration of a Robust and Prognostic Immune Related Gene Signature for Cervical Squamous Cell Carcinoma.

Background: Cervical squamous cell carcinoma (CESC) is one of the most frequent malignancies in women worldwide. The level of immune cell infiltration and immune-related genes (IRGs) can significantly affect the prognosis and immunotherapy of CESC patients. Thus, this study aimed to identify an immune-related prognostic signature for CESC. Methods: TCGA-CESC cohorts, obtained from TCGA database, were divided into the training group and testing group; while GSE44001 dataset from GEO database was viewed as external validation group. ESTIMATE algorithm was applied to evaluate the infiltration levels of immune cells of CESC patients. IRGs were screened out through weighted gene co-expression network analysis (WGCNA). A multi-gene prognostic signature based on IRGs was constructed using LASSO penalized Cox proportional hazards regression, which was validated through Kaplan-Meier, Cox, and receiver operating characteristic curve (ROC) analyses. The abundance of immune cells was calculated using ssGSEA algorithm in the ImmuCellAI database, and the response to immunotherapy was evaluated using immunophenoscore (IPS) analysis and the TIDE algorithm. Results: In TCGA-CESC cohorts, higher levels of immune cell infiltration were closely associated with better prognoses. Moreover, a prognostic signature was constructed using three IRGs. Based on this given signature, Kaplan-Meier analysis suggested the significant differences in overall survival (OS) and the ROC analysis demonstrated its robust predictive potential for CESC prognosis, further confirmed by internal and external validation. Additionally, multivariate Cox analysis revealed that the three IRGs signature served as an independent prognostic factor for CESC. In the three-IRGs signature low-risk group, the infiltrating immune cells (B cells, CD4/8 + T cells, cytotoxic T cells, macrophages and so on) were much more abundant than that in high-risk group. Ultimately, IPS and TIDE analyses showed that low-risk CESC patients appeared to present with a better response to immunotherapy and a better prognosis than high-risk patients. Conclusion: The present prognostic signature based on three IRGs (CD3E, CD3D, LCK) was not only reliable for survival prediction but efficient to predict the clinical response to immunotherapy for CESC patients, which might assist in guiding more precise individual treatment in the future.

An enzyme-powered, three-dimensional lame DNA walker.

Molecular machines constructed by three-dimensional (3-D) DNA walker have emerged as a hot topic in applications such as novel biosensors, cargo delivery platforms and intracellular imaging. Herein, we first propose a lame DNA walker that can randomly and autonomously move on microsphere-based 3-D track. The stochastic lame walker has a long leg mainly responsible for persistent movement and a short leg cutting substrates rapidly. Its motion is propelled by a nicking endonuclease cleavage of hybridized DNA tracks. Kinetic and persistent study show that the lame DNA walker enables reaction equilibrium at 30 min, need a cleat domain of at least 14 nucleotides and can persistently move on 3-D tracks with an average rate of 6.467 × 10-11 M s-1. We also demonstrate that the lame walker can be used to detect target DNA in the detection range of 10 pM-5 nM with high specificity by toehold exchange mechanism. This work will further expand the performance of 3-D DNA walkers and substantially contributes to the improved understanding of DNA walking systems.

A nanoprobe for fluorescent monitoring of microRNA and targeted delivery of drugs.

Multifunctional nano-materials that can be used to monitor the expression of specific biomarkers and serve as vehicles for controlled drug delivery are highly desirable. Herein, we report a new DNA-hybrid-gated core-shell upconversion nanoprobe (UCNP@MOF/DOX) for fluorescence analysis of microRNA-21 (miR-21), which also triggers the release of drug loaded in the probes for on-demand anti-cancer treatment. The nanoprobe is built on the merits of ultraviolet-visible light of upconversion nanoparticles (UCNPs) excited by near-infrared (NIR) and extraordinary loading capability of metal-organic frameworks (MOFs) for drug delivery. Controlled release of doxorubicin (DOX) from the nanoprobe by miR-21 underwent the following two-stage kinetics: a fast release stage specifically triggered by miR-21 and proportional to miR-21 concentration and a slow stage observed in both gated and ungated nanoprobes due to collapse of the UIO-66-NH2 coatings via ligand exchange with phosphates. In addition, the nanoprobe showed good selectivity, a linear response towards miR-21 ranging from 4 nM to 500 nM, and a limit of detection in 4 nM, which precluded unintended payload leakage due to low-abundance endogenous miR-21 expression in normal cells. Moreover, based on a dual-targeted delivery system constituted by AS1411-mediated recognition and responsive release of DOX, a specific cytotoxic efficacy was observed in MCF-7 cells. The present work provides a smart and robust nanoprobe for real-time detection of miRNA and dual-responsive drug delivery in tumor cells.

Tumor promoting effects of circRNA_001287 on renal cell carcinoma through miR-144-targeted CEP55.

BACKGROUND: Renal cell carcinoma (RCC) is a common urological cancer. circular RNAs (circRNAs) is involved in the development of various types of cancers. However, the roles and underlying mechanisms of circRNAs in RCC are not fully elucidated. Herein, we aimed to examine the potential effect of circ_001287 on RCC progression. MATERIALS AND METHODS: Microarray-based gene expression profiling of RCC was initially employed in order to identify differentially expressed genes. Next, the expression of circ_001287 was examined, and the cell line with the highest circ_001287 expression was selected for subsequent investigation. The interaction among circ_001287, miR-144, and CEP55 was identified by conducting luciferase reporter assay, RNA-pull down, RIP, RT-qPCR and FISH. The effect of circ_001287 on proliferative, invasive and migratory capacities as well as tumorigenicity of transfected cells in mice was examined using gain- and loss-of-function experiments. RESULTS: circ_001287 and CEP55 were highly expressed while miR-144 was decreased in RCC tissues and cell lines. circ_001287 can up-regulate CEP55 by binding to miR-144, which resulted in increased proliferative, invasive and migratory capacities and tumor growth in vivo. In addition, down-regulation of miR-144 was also observed to promote these biological activities. CONCLUSIONS: Overall, these results elucidate a new mechanism for circ_001287 in RCC development and provide a potential therapeutic target for RCC patients.

A Nomogram for the Prediction of Progression and Overall Survival in Childhood Acute Lymphoblastic Leukemia.

Background: Advances in treatment and supportive care have significantly improved the overall survival (OS) of pediatric patients with acute lymphoblastic leukemia (ALL). However, there is a large number of these patients who continue to relapse after receiving standard treatment. Accurate identification of patients at high risk of relapse and targeted therapy may significantly improve their prognosis. Therefore, the aim of this study was to identify significant prognostic factors for pediatric ALL and establish a novel nomogram for the prediction of survival. Methods: The ALL clinical data of Phases I and II of the Therapeutic Applicable Research to Generate Effective Treatments (TARGET) project were merged and randomly divided into training and validation groups. The LASSO regression model was used to select the specific factors related to the OS of the training group and generate prognostic nomograms according to the selected characteristics. The predictive accuracy of the nomogram for OS was verified using the concordance index of the training and validation groups, the area under the receiver operating characteristic curve for prognostic diagnosis, and the calibration curve. Results: A total of 1,000 children with ALL were included in the TARGET project. Of those, 489 patients had complete follow-up data for further analysis. The data were randomly divided into the training group (n = 345) and the validation group (n = 144). Seven clinical characteristics, namely age at diagnosis, peripheral white blood cells, bone marrow and CNS site of relapse, ETV6/RUNX1 fusion, TCF3/PBX1, and BCR/ABL1 status, were selected to construct the nomogram. The concordance indices of the training and validation groups were 0.809 (95% confidence interval: 0.766-0.852) and 0.826 (95% confidence interval: 0.767-0.885), respectively. The areas under the receiver operating characteristic curve of the 3-year, 5-year, and 10-year OS in the training group were 0.804, 0.848, and 0.885, respectively, while that of the validation group were 0.777, 0.825, and 0.863, respectively. Moreover, the calibration curves demonstrated a favorable consistency between the predicted and actual survival probabilities. Conclusions: Independent predictors of OS in children with ALL included age at diagnosis, white blood cells, bone marrow site of relapse, CNS site of relapse, ETV6/RUNX1 fusion, TCF3/PBX1, and BCR/ABL1 status. The nomograms developed using these high-risk factors can more simply, accurately, and quantitatively predict the survival of children, and improve treatment and prognosis.