Cancer-derived exosomal lncRNA SNHG3 promotes the metastasis of colorectal cancer through hnRNPC-mediating RNA stability of ß-catenin.

Metastasis is the leading cause of death in colorectal cancer (CRC) patients. By mediating intercellular communication, exosomes exhibit considerable value in regulating tumor metastasis. Long non-coding RNAs (lncRNAs) are abundant in exosomes and participate in regulating tumor progression. However, it is poorly understood how the cancer-secreted exosomal lncRNAs affect CRC proliferation and metastasis. Here, by analyzing the public databases we identified a lncRNA SNHG3 and demonstrated that SNHG3 was delivered through CRC cells-derived exosomes to promote metastasis in CRC. Mechanistically, exosomal SNHG3 was internalized by CRC cells and afterward upregulated the expression of ß-catenin by facilitating the intranuclear transport of hnRNPC. Consequently, the RNA stability of ß-catenin was enhanced which led to the activation of EMT and metastasis of CRC cells. Our findings expand the oncogenic mechanisms of exosomal SNHG3 and identify it as a diagnostic marker for CRC.

Decarboxylative Nucleophilic Fluorination of Aliphatic Carboxylic Acids.

Herein, we present a decarboxylative nucleophilic fluorination of carboxylic acids with a silver catalyst. This strategy enables the synthesis of a myriad of diverse and valuable fluorinated motifs under mild conditions, demonstrating good functional-group tolerance and utility in late-stage functionalization. In contrast to traditional electrophilic fluorination, this nucleophilic method utilizes a more readily available nucleophilic fluorinating reagent, providing substantial advantages in terms of cost efficiency, broad substrate scope, and functional-group compatibility.

Inhibition of co-occurring weeds and young sugarcane seedling growth by perennial sugarcane root extract.

Allelopathy is a process whereby a plant directly or indirectly promotes or inhibits growth of surrounding plants. Perennial sugarcane root extracts from various years significantly inhibited Bidens pilosa, Digitaria sanguinalis, sugarcane stem seedlings, and sugarcane tissue-cultured seedlings (P < 0.05), with maximum respective allelopathies of - 0.60, - 0.62, - 0.20, and - 0.29. Allelopathy increased with increasing concentrations for the same-year root extract, and inhibitory effects of the neutral, acidic, and alkaline components of perennial sugarcane root extract from different years were significantly stronger than those of the control for sugarcane stem seedlings (P < 0.05). The results suggest that allelopathic effects of perennial sugarcane root extract vary yearly, acids, esters and phenols could be a main reason for the allelopathic autotoxicity of sugarcane ratoons and depend on the type and content of allelochemicals present, and that allelopathy is influenced by other environmental factors within the rhizosphere such as the presence of old perennial sugarcane roots. This may be a crucial factor contributing to the decline of perennial sugarcane root health.

Comprehensive multi-omics analysis and experimental verification reveal PFDN5 is a novel prognostic and therapeutic biomarker for gastric cancer.

Prefoldin Subunit 5 (PFDN5) plays a critical role as a member of the prefoldins (PFDNs) in maintaining a finely tuned equilibrium between protein production and degradation. However, there has been no comprehensive analysis specifically focused on PFDN5 thus far. Here, a comprehensive multi-omics (transcriptomics, genomics, and proteomics) analysis, systematic molecular biology experiments (in vitro and in vivo), transcriptome sequencing and PCR Array were performed for identifying the value of PFDN5 in pan-cancer, especially in Gastric Cancer (GC). We found PFDN5 had the potential to serve as a prognostic and therapeutic biomarker in GC. And PFDN5 could promote the proliferation of GC cells, primarily by affecting the cell cycle, cell death and immune process etc. These findings provide novel insights into the molecular mechanisms and precise treatments of in GC.

Utilizing machine learning for reactive material selection and width design in permeable reactive barrier (PRB).

Permeable reactive barrier (PRB) is an important groundwater treatment technology. However, selecting the optimal reactive material and estimating the width remain critical and challenging problems in PRB design. Machine learning (ML) has advantages in predicting evolution and tracing contaminants in temporal and spatial distribution. In this study, ML was developed to design PRB, and its feasibility was validated through experiments and a case study. ML algorithm showed a good prediction about the Freundlich equilibrium parameter (R2 0.94 for KF, R2 0.96 for n). After SHapley Additive exPlanation (SHAP) analysis, redefining the range of the significant impact factors (initial concentration and pH) can further improve the prediction accuracy (R2 0.99 for KF, R2 0.99 for n). To mitigate model bias and ensure comprehensiveness, evaluation index with expert opinions was used to determine the optimal material from candidate materials. Meanwhile, the ML algorithm was also applied to predict the width of the mass transport zone in the adsorption column. This procedure showed excellent accuracy with R2 and root-mean-square-error (RMSE) of 0.98 and 1.2, respectively. Compared with the traditional width design methodology, ML can enhance design efficiency and save experiment time. The novel approach is based on traditional design principles, and the limitations and challenges are highlighted. After further expanding the data set and optimizing the algorithm, the accuracy of ML can make up for the existing limitations and obtain wider applications.

Predicting multiple linear stapler firings in double stapling technique with an MRI-based deep-learning model.

Multiple linear stapler firings is a risk factor for anastomotic leakage (AL) in laparoscopic low anterior resection (LAR) using double stapling technique (DST) anastomosis. In this study, our objective was to establish the risk factors for ≥ 3 linear stapler firings, and to create and validate a predictive model for ≥ 3 linear stapler firings in laparoscopic LAR using DST anastomosis. We retrospectively enrolled 328 mid-low rectal cancer patients undergoing laparoscopic LAR using DST anastomosis. With a split ratio of 4:1, patients were randomly divided into 2 sets: the training set (n = 260) and the testing set (n = 68). A clinical predictive model of ≥ 3 linear stapler firings was constructed by binary logistic regression. Based on three-dimensional convolutional networks, we built an image model using only magnetic resonance (MR) images segmented by Mask region-based convolutional neural network, and an integrated model based on both MR images and clinical variables. Area under the curve (AUC), sensitivity, specificity, accuracy, positive predictive value (PPV), and Youden index were calculated for each model. And the three models were validated by an independent cohort of 128 patients. There were 17.7% (58/328) patients received ≥ 3 linear stapler firings. Tumor size ≥ 5 cm (odds ratio (OR) = 2.54, 95% confidence interval (CI) = 1.15-5.60, p = 0.021) and preoperative carcinoma embryonic antigen (CEA) level > 5 ng/mL [OR = 2.20, 95% CI = 1.20-4.04, p = 0.011] were independent risk factors associated with ≥ 3 linear stapler firings. The integrated model (AUC = 0.88, accuracy = 94.1%) performed better on predicting ≥ 3 linear stapler firings than the clinical model (AUC = 0.72, accuracy = 86.7%) and the image model (AUC = 0.81, accuracy = 91.2%). Similarly, in the validation set, the integrated model (AUC = 0.84, accuracy = 93.8%) performed better than the clinical model (AUC = 0.65, accuracy = 65.6%) and the image model (AUC = 0.75, accuracy = 92.1%). Our deep-learning model based on pelvic MR can help predict the high-risk population with ≥ 3 linear stapler firings in laparoscopic LAR using DST anastomosis. This model might assist in determining preoperatively the anastomotic technique for mid-low rectal cancer patients.

Exploring the relationship between lactate metabolism and immunological function in colorectal cancer through genes identification and analysis.

Introduction: Metabolic dysregulation is a widely acknowledged contributor for the development and tumorigenesis of colorectal cancer (CRC), highlighting the need for reliable prognostic biomarkers in this malignancy. Methods: Herein, we identified key genes relevant to CRC metabolism through a comprehensive analysis of lactate metabolism-related genes from GSEA MsigDB, employing univariate Cox regression analysis and random forest algorithms. Clinical prognostic analysis was performed following identification of three key genes, and consistent clustering enabled the classification of public datasets into three patterns with significant prognostic differences. The molecular pathways and tumor microenvironment (TME) of these patterns were then investigated through correlation analyses. Quantitative PCR was employed to quantify the mRNA expression levels of the three pivotal genes in CRC tissue. Single-cell RNA sequencing data and fluorescent multiplex immunohistochemistry were utilized to analyze relevant T cells and validate the correlation between key genes and CD4+ T cells. Results: Our analysis revealed that MPC1, COQ2, and ADAMTS13 significantly stratify the cohort into three patterns with distinct prognoses. Additionally, the immune infiltration and molecular pathways were significantly different for each pattern. Among the key genes, MPC1 and COQ2 were positively associated with good prognosis, whereas ADAMTS13 was negatively associated with good prognosis. Single-cell RNA sequencing (scRNA-seq) data illustrated that the relationship between three key genes and T cells, which was further confirmed by the results of fluorescent multiplex immunohistochemistry demonstrating a positive correlation between MPC1 and COQ2 with CD4+ T cells and a negative correlation between ADAMTS13 and CD4+ T cells. Discussion: These findings suggest that the three key lactate metabolism genes, MPC1, COQ2, and ADAMTS13, may serve as effective prognostic biomarkers and support the link between lactate metabolism and the immune microenvironment in CRC.

Stabilizing Cr(â ¢) deriving from tannery sludge with kaolin and organic matter.

Stabilizing Cr(III) in tannery sludge (TS) via harmless method has always been the goal of environmental pollution treatment. In this study, a simple method to stabilize Cr(III) in TS is proposed via adding kaolin, based on the fact a large amount of organic matter contained in TS. Comprehensive characterizations confirm that kaolin can stabilize Cr(Ⅲ) via its abundant -OH and lamellar structure. Moreover, there are hydrogen bond interactions and ligand exchange-surface complexation between organic matter and kaolin, which is more conducive to form a stable ternary complex with Cr(III), in a state of organic matter-Cr(III)-kaolin. Simultaneously, the BCR sequential extraction experiment shows that the unstable water and acid soluble state of Cr(III) are reduced (from 0.61% to 0.35%), which further indicates that the stabilization of Cr(III) is successful.

Alterations of gut microbiota in biopsy-proven diabetic nephropathy and a long history of diabetes without kidney damage.

The gut microbiota is closely related to parenteral noncommunicable diseases through intestinal immunity and plays an important role in the occurrence of diabetes and diabetic nephropathy. The aim of the study was to understand the gut-kidney axis by an analysis of gut microbiota composition among patients with biopsy-proven diabetic nephropathy (DN), patients with type 2 diabetes for more than 10 years without kidney damage (DM), and healthy controls (NC). Thirty-five DN patients, 40 DM patients and 40 healthy subjects matched by age and sex were enrolled between January 2022 and December 2022. Baseline information and clinical parameters were collected. 16S rDNA sequencing was performed to characterize the gut microbiome and identify gut microbes that were differentially abundant between patients and healthy controls. The relationship between the relative abundance of specific bacterial taxa in the gut and clinical phenotype and pathological indicators was evaluated. Substantial differences were found in the richness of the gut microbiota and the variation in the bacterial population among DN patients, DM patients and healthy controls. DM patients could be accurately distinguished from age- and sex-matched healthy controls by variations in g_Clostridium-XVIII (AUC = 0.929), and DN patients could be accurately distinguished from age- and sex-matched healthy controls by variations in g_Gemmiger (AUC = 0.842). DN patients could be accurately distinguished from age- and sex-matched DM patients by variations in g_Flavonifractor or g_Eisenbergiella (AUC = 0.909 and 0.886, respectively). The gut microbiota was also closely related to clinical phenotypes and pathological indicators. The study of gut microbiota composition was explored to determine its relationship to the occurrence of DN and a long history of diabetes without kidney damage. The renal pathological progression of DN may be delayed by regulating changes in the gut microbiota.

Is Pathologic Complete Response a Good Predictor for the Long-Term, Clinical Outcome in Patients with Gastric Cancer After Neoadjuvant Chemotherapy? A Retrospective, Multi-institution Study in China.

BACKGROUND: Many studies have used pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) as the primary endpoint for the short-term efficacy in gastric cancer, but whether it is a good indicator for overall survival is poorly understood. METHODS: This study reviewed a multi-institution database of patients who underwent radical gastrectomy and achieved pCR after NAC. Cox regression models were used to identify clinicopathologic predictors of overall survival (OS) and disease-free survival (DFS). Survival curves were calculated by using the Kaplan-Meier method and compared by means of the log-rank test. RESULTS: OS and DFS in patients with pCR were significantly higher than in those with non-pCR (both P < 0.001). Multivariable analysis confirmed pCR was an independent prognostic factor for OS and DFS (P = 0.009 and P = 0.002 for OS and DFS, respectively). However, the survival benefit for pCR was present only for ypN0 tumors (P = 0.004 and P = 0.001 for OS and DFS, respectively), and OS (P = 0.292) and DFS (P = 0.285) among patients with ypN+ gastric cancer could not be stratified by pCR. CONCLUSIONS: In our study, pCR is an independent prognostic factor for OS and DFS, but the survival benefit for pCR is present only for ypN0 tumors but not ypN+ tumors.

Exploring the role of pyroptosis in shaping the tumor microenvironment of colorectal cancer by bulk and single-cell RNA sequencing.

BACKGROUND: Emerging studies have shown that pyroptosis plays a non-negligible role in the development and treatment of tumors. However, the mechanism of pyroptosis in colorectal cancer (CRC) remains still unclear. Therefore, this study investigated the role of pyroptosis in CRC. METHODS: A pyroptosis-related risk model was developed using univariate Cox regression and LASSO Cox regression analyses. Based on this model, pyroptosis-related risk scores (PRS) of CRC samples with OS time > 0 from Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database were calculated. The abundance of immune cells in CRC tumor microenvironment (TME) was predicted by single-sample gene-set enrichment analysis (ssGSEA). Then, the responses to chemotherapy and immunotherapy were predicted by pRRophetic algorithm, the tumor immune dysfunction and exclusion (TIDE) and SubMap algorithms, respectively. Moreover, the Cancer Therapeutics Response Portal (CTRP) and PRISM Repurposing dataset (PRISM) were used to explore novel drug treatment strategies of CRC. Finally, we investigated pyroptosis-related genes in the level of single-cell and validated the expression levels of these genes between normal and CRC cell lines by RT-qPCR. RESULTS: Survival analysis showed that CRC samples with low PRS had better overall survival (OS) and progression-free survival (PFS). CRC samples with low PRS had higher immune-related gene expression and immune cell infiltration than those with high PRS. Besides, CRC samples with low PRS were more likely to benefit from 5-fluorouracil based chemotherapy and anti-PD-1 immunotherapy. In novel drug prediction, some compounds such as C6-ceramide and noretynodrel, were inferred as potential drugs for CRC with different PRS. Single-cell analysis revealed pyroptosis-related genes were highly expressed in tumor cells. RT-qPCR also demonstrated different expression levels of these genes between normal and CRC cell lines. CONCLUSIONS: Taken together, this study provides a comprehensive investigation of the role of pyroptosis in CRC at the bulk RNA sequencing (RNA-seq) and single-cell RNA sequencing (scRNA-seq) levels, advances our understanding of CRC characteristics, and guides more effective treatment regimens.

Comparison of effects of multiple oxidants with an ultrasonic system under unified system conditions for bisphenol A degradation.

Bisphenol A (BPA) as a trace contaminant has been reported, due to widespread use in the plastics industry. This study applied the 35 kHz ultrasound (US) to activate four different common oxidants (H2O2, HSO5-, S2O82-, and IO4-) for BPA degradation. With increasing initial concentration of oxidants, the degradation rate of BPA increased. The synergy index confirmed that a synergistic relationship between US and oxidants. This study also examined the impact of pH and temperature. The results showed that the kinetic constants of US, US-H2O2, US-HSO5- and US-IO4-decreased when the pH increased from 6 to 11. The optimal pH for US-S2O82- was 8. Notably, increasing temperature decreased the performance of US, US-H2O2, and US-IO4- systems, while it could increase the degradation of BPA in US-S2O82- and US-HSO5-. The activation energy for BPA decomposition using the US-IO4- system was the lowest, at 0.453nullkJnullmol-1, and the synergy index was the highest at 2.22. Additionally, the ΔG# value was found to be 2.11 + 0.29T when the temperature ranged from 25 °C to 45 °C. The main oxidation contribution is achieved by hydroxyl radicals in scavenger test. The mechanism of activation of US-oxidant is heat and electron transfer. In the case of the US-IO4- system, the economic analysis yielded 271 kwh m-3, which was approximately 2.4 times lower than that of the US process.

Zero-valent iron based materials selection for permeable reactive barrier using machine learning.

The zero-valent iron (ZVI) based reactive materials are potential remediation reagents in permeable reactive barriers (PRB). Considering that reactive materials is the essential to determining the long-term stability of PRB and the emergence of a large number of new iron-based materials. Here, we present a new approach using machine learning to screen PRB reactive materials, which proposes to improve the efficiency and practicality of selection of ZVI-based materials. To compensate for the insufficient amount of existing machine learning source data and the real-world implementation, machine learning combines evaluation index (EI) and reactive material experimental evaluations. XGboost model is applied to estimate the kinetic data and SHAP is used to improve the accuracy of model. Batch and column tests were conducted to investigate the geochemical characteristics of groundwater. The study find that specific surface area is a fundamental factor correlated with the kinetic constants of ZVI-based materials, according to SHAP analysis. Reclassifying the data with specific surface area significantly improved prediction accuracy (reducing RMSE from 1.84 to 0.6). Experimental evaluation results showed that ZVI had 3.2 times higher anaerobic corrosion reaction kinetic constants and 3.8 times lower selectivity than AC-ZVI. Mechanistic studies revealed the transformation pathways and endpoint products of iron compounds. Overall, this study is a successful initial attempt to use machine learning for selecting reactive materials.

Infrapyloric (No. 206) and greater curvature (No. 204) lymph node metastasis in adenocarcinoma located in the right half of the transverse colon (InCLART Study): protocol for a multicentre prospective observational study.

INTRODUCTION: In the case of right-sided transverse colon cancer (RTCC) and hepatic flexure colon cancer (HFCC), there is a potential connection of lymph drainage between mesentery and greater omentum. However, most previous reports have been limited case series with No. 206 and No. 204 lymph node (LN) dissection for RTCC and HFCC. METHODS AND ANALYSIS: The InCLART Study is a prospective observational study aiming to enrol 427 patients with RTCC and HFCC treated at 21 high-volume institutions in China. The prevalence of infrapyloric (No. 206) and greater curvature (No. 204) LN metastasis and short-term outcomes will be investigated in a consecutive series of patients with T2 or deeper invasion RTCC or HFCC, following the principle of complete mesocolic excision with central vascular ligation. Primary endpoints were performed to identify the prevalence of No. 206 and No. 204 LN metastasis. Secondary analyses will be used to estimate prognostic outcomes, intraoperative and postoperative complications, the consistency of preoperative evaluation and postoperative pathological results of LN metastasis. ETHICS AND DISSEMINATION: Ethical approval for the study has been granted by the Ruijin Hospital Ethics Committee (approval number: 2019-081) and has been or will be approved successively by each participating centre's Research Ethics Board. The findings will be disseminated in peer-reviewed publications. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov Registry (NCT03936530; https://clinicaltrials.gov/ct2/show/NCT03936530).

Magnetic resonance imaging-based deep learning model to predict multiple firings in double-stapled colorectal anastomosis.

BACKGROUND: Multiple linear stapler firings during double stapling technique (DST) after laparoscopic low anterior resection (LAR) are associated with an increased risk of anastomotic leakage (AL). However, it is difficult to predict preoperatively the need for multiple linear stapler cartridges during DST anastomosis. AIM: To develop a deep learning model to predict multiple firings during DST anastomosis based on pelvic magnetic resonance imaging (MRI). METHODS: We collected 9476 MR images from 328 mid-low rectal cancer patients undergoing LAR with DST anastomosis, which were randomly divided into a training set (n = 260) and testing set (n = 68). Binary logistic regression was adopted to create a clinical model using six factors. The sequence of fast spin-echo T2-weighted MRI of the entire pelvis was segmented and analyzed. Pure-image and clinical-image integrated deep learning models were constructed using the mask region-based convolutional neural network segmentation tool and three-dimensional convolutional networks. Sensitivity, specificity, accuracy, positive predictive value (PPV), and area under the receiver operating characteristic curve (AUC) was calculated for each model. RESULTS: The prevalence of ≥ 3 linear stapler cartridges was 17.7% (58/328). The prevalence of AL was statistically significantly higher in patients with ≥ 3 cartridges compared to those with ≤ 2 cartridges (25.0% vs 11.8%, P = 0.018). Preoperative carcinoembryonic antigen level > 5 ng/mL (OR = 2.11, 95%CI 1.08-4.12, P = 0.028) and tumor size ≥ 5 cm (OR = 3.57, 95%CI 1.61-7.89, P = 0.002) were recognized as independent risk factors for use of ≥ 3 linear stapler cartridges. Diagnostic performance was better with the integrated model (accuracy = 94.1%, PPV = 87.5%, and AUC = 0.88) compared with the clinical model (accuracy = 86.7%, PPV = 38.9%, and AUC = 0.72) and the image model (accuracy = 91.2%, PPV = 83.3%, and AUC = 0.81). CONCLUSION: MRI-based deep learning model can predict the use of ≥ 3 linear stapler cartridges during DST anastomosis in laparoscopic LAR surgery. This model might help determine the best anastomosis strategy by avoiding DST when there is a high probability of the need for ≥ 3 linear stapler cartridges.

Theoretical and Experimental Investigation on the Flexural Behaviour of Prestressed NC-UHPC Composite Beams.

To investigate the normal section strength and cracking bending moment of normal concrete-ultra-high-performance concrete (NC-UHPC) composite beams, calculation formulas were established considering the tensile strength of UHPC based on the current railway bridge design code. Using the railway T-beam as a template, prestressed NC-UHPC composite beams with different NC layer heights were built. A static bending test was performed, the pressure of the steel strand and the deflection and strain of the beam were measured, and the evolution of cracks in each beam was observed. The calculation formulas of the normal section strength and cracking bending moment of NC-UHPC composite beam were verified by the test. The results showed that the type of strain was similar to load-deflection curves with increasing load; the bending failure process of the NC-UHPC composite beam showed four obvious stages: elasticity, uniform cracking, crack development, and yield. Cracks in the beam started to appear at stage II, developed rapidly at stage III, and stopped emerging at stage IV. The calculation formulas for the normal section strength and the cracking bending moment of the NC-UHPC composite beam were in good agreement with the test values. Normal concrete with a compressive strength of 80 MPa can replace UHPC for the design of NC-UHPC composite beams.

Synthesis of Benzylic Alcohols by Decarboxylative Hydroxylation.

Herein, we demonstrate an efficient method for the decarboxylative hydroxylation of carboxylic acids with silver(I) as the catalyst and cerium ammonium nitrate as the oxidant and its utility in chemoselective late-stage functionalization of natural products and drug molecules. The chemoselectivity of this protocol arises from a benzylic nitrate intermediate that retards further oxidation and is hydrolyzed to the final benzylic alcohol product. Mechanistic investigation reveals that the facile oxidation of silver carboxylate affords silver(II) species as an intermediate oxidant responsible for decarboxylation.

Associations of genetic variants contributing to gut microbiota composition in diabetic nephropathy.

Introduction: The gut microbiota is strongly associated with multiple kidney diseases, and since microbial composition is heritable, we hypothesized that genetic variations controlling gut microbiota composition were associated with diabetic nephropathy susceptibility or clinical subphenotypes. Methods: The genetic variations associated with gut microbiota were retrieved from the genome-wide association study database and analysed in our diabetic nephropathy susceptibility gene screening cohort. Candidate microorganisms with possible genetic associations were identified using the annotation of microbial quantitative trait loci. Finally, the candidate microorganisms were verified by 16S rDNA gene sequencing. Results: There were 13 genetic variation loci associated with susceptibility to diabetic nephropathy. The TCF7L2 risk genotype was associated with a long duration of diabetes and high diastolic blood pressure, the ZCWPW2 risk genotype was associated with increased glycosylated hemoglobin, and the ZNRF3 risk genotype was associated with an increased urinary microalbumin-to-creatinine ratio. Both the ZNRF3 and SPECC1L risk genotypes were associated with the abundance of Lactococcus. 16S rDNA sequencing confirmed that there was indeed a significant difference in the Lactococcus genus between DN and DM patients. Conclusions: In this study, we preliminarily confirmed that the gut microbiota of diabetic nephropathy patients is influenced by host genetics and provide a new basis for future accurate diagnosis and treatment.

LncRNA LENGA acts as a tumor suppressor in gastric cancer through BRD7/TP53 signaling.

It has been established that long noncoding RNAs (lncRNAs) play a crucial role in various cancer types, and there are vast numbers of long noncoding RNA transcripts that have been identified by high-throughput methods. However, the biological function of many novel aberrantly expressed lncRNAs remains poorly elucidated, especially in gastric cancer (GC). Here, we first identified a novel lncRNA termed LENGA (Low Expression Noncoding RNA in Gastric Adenocarcinoma), which was significantly downregulated in GC tissues compared to adjacent normal tissues. Next, we found that reduced expression of LENGA in GC was also associated with a shorter life expectancy. The proliferation, migration, and invasion of GC cells were increased after LENGA knockdown but restrained after LENGA overexpression in vitro and in vivo. It was further demonstrated that LENGA physically binds to BRD7 (bromodomain-containing 7) in the bromodomain domain and acts as a scaffold that enhances the interaction between BRD7 and TP53 (tumor protein p53), regulating the expression of a subset of genes in the p53 pathway, including CDKN1A (cyclin-dependent kinase inhibitor 1A) and PCDH7 (protocadherin 7), at the transcriptional level. Consistently, the expression of CDKN1A has a positive correlation with LENGA in GC patients. Taken together, this study uncovers a novel tumor suppressor lncRNA, LENGA, and describes its biological function, molecular mechanism, and clinical significance. This highlights the potential importance of targeting the LENGA/BRD7/TP53 axis in GC treatment.