Success rate of current human-derived gastric cancer organoids establishment and influencing factors: A systematic review and meta-analysis.

BACKGROUND: Human-derived gastric cancer organoids (GCOs) are widely used in gastric cancer research; however, the culture success rate is generally low. AIM: To explore the potential influencing factors, and the literature on successful culture rates of GCOs was reviewed using meta-analysis. METHODS: PubMed, Web of Science, and EMBASE were searched for studies. Two trained researchers selected the studies and extracted data. STATA 17.0 software was used for meta-analysis of the incidence of each outcome event. The adjusted Methodological Index for Non-Randomized Studies scale was used to assess the quality of the included studies. Funnel plots and Egger's test were used to detect publication bias. Subgroup analyses were conducted for sex, tissue source, histological classification, and the pathological tumor-node-metastasis (pTNM) cancer staging system. RESULTS: Eight studies with a pooled success rate of 66.6% were included. GCOs derived from women and men had success rates of 67% and 46.7%, respectively. GCOs from surgery or biopsy/endoscopic submucosal dissection showed success rates of 70.9% and 53.7%, respectively. GCOs of poorly-differentiated, moderately-differentiated and signet-ring cell cancer showed success rates of 64.6%, 31%, and 32.7%, respectively. GCOs with pTNM stages I-II and III-IV showed success rates of 38.3% and 65.2%, respectively. Y-27632 and non-Y-27632 use showed success rates of 58.2% and 70%, respectively. GCOs generated with collagenase were more successful than those constructed with Liberase TH and TrypLE (72.1% vs 71%, respectively). EDTA digestion showed a 50% lower success rate than other methods (P = 0.04). CONCLUSION: GCO establishment rate is low and varies by sex, tissue source, histological type, and pTNM stage. Omitting Y-27632, and using Liberase TH, TrypLE, or collagenase yields greater success than EDTA.

Bibliometrics analysis based on the Web of Science: Current trends and perspective of gastric organoid during 2010-2023.

BACKGROUND: Three-dimensional organoid culture systems have been established as a robust tool for elucidating mechanisms and performing drug efficacy testing. The use of gastric organoid models holds significant promise for advancing personalized medicine research. However, a comprehensive bibliometric review of this bur-geoning field has not yet been published. AIM: To analyze and understand the development, impact, and direction of gastric organoid research using bibliometric methods using data from the Web of Science Core Collection (WoSCC) database. METHODS: This analysis encompassed literature pertaining to gastric organoids published between 2010 and 2023, as indexed in the WoSCC. CiteSpace and VOSviewer were used to depict network maps illustrating collaborations among authors, institutions and keywords related to gastric organoid. Citation, co-citation, and burst analysis methodologies were applied to assess the impact and progress of research. RESULTS: A total of 656 relevant studies were evaluated. The majority of research was published in gastroenterology-focused journals. Globally, Yana Zavros, Hans Clevers, James M Wells, Sina Bartfeld, and Chen Zheng were the 5 most productive authors, while Hans Clevers, Huch Meritxell, Johan H van Es, Marc Van de Wetering, and Sato Toshiro were the foremost influential scientists in this area. Institutions from the University Medical Center Utrecht, Netherlands Institute for Developmental Biology (Utrecht), and University of Cincinnati (Cincinnati, OH, United States) made the most significant contributions. Currently, gastric organoids are used mainly in studies investigating gastric cancer (GC), Helicobacter pylori-infective gastritis, with a focus on the mechanisms of GC, and drug screening tests. CONCLUSION: Key focus areas of research using gastric organoids include unraveling disease mechanisms and enhancing drug screening techniques. Major contributions from renowned academic institutions highlight this field's dynamic growth.

Chaihu Shugan Powder inhibits interstitial cells of cajal mitophagy through USP30 in the treatment of functional dyspepsia.

ETHNOPHARMACOLOGICAL RELEVANCE: Chaihu Shugan Powder (CHSGP) has significant clinical efficacy in the treatment of functional dyspepsia (FD), but the specific mechanism requires further study. AIM OF STUDY: The aim of this study was to investigate the therapeutic effect of CHSGP on FD rats and the underlying mechanism of the effect on interstitial cells of cajal (ICC) mitophagy. MATERIALS AND METHODS: The tail-clamping stimulation method was utilized to establish an FD rat model in vivo. Gastric emptying rate and small intestinal propulsion rate test, H&E staining, and Immunohistochemistry were conducted to evaluate the therapeutic effects of CHSGP on FD rats. In vitro, the regulatory effect of CHSGP on CCCP-mediated ICC mitophagy was further investigated by CCK8, Transmission electron microscope, immunofluorescence co-staining, Quantitative polymerase chain reaction and Western blot to reveal the potential mechanisms of CHSGP inhibited ICC mitophagy. RESULTS: Animal experiments provided evidence that CHSGP promoted gastric motility, increased ICC numbers, reduced Parkin expression, and elevated USP30 expression in FD rats. In vitro, further mechanism research demonstrated that CHSGP decreased LC3Ⅱ/LC3Ⅰ、PINK1、Parkin、PHB2 protein expression and increased USP30 protein expression. Furthermore, CHSGP increased Mfn2 protein expression by suppressing activation of the PINK1/Parkin pathway when USP30 is knocked down, consequently reducing CCCP-induced ICC mitophagy. CONCLUSIONS: These results suggest that CHSGP may treat FD against CCCP-induced ICC mitophagy by the up-regulation of via PINK1/Parkin pathway.

Network pharmacology and experimental studies for deciphering the molecular targets and mechanisms of Chaihu Shugan powder in the treatment of functional dyspepsia.

BACKGROUND: Chaihu Shugan powder (CSP) is a prevalent prescription product used in the treatment functional dyspepsia (FD) in China. However, the underlying pharmacological mechanisms involved in the treatment of FD remain unclear. OBJECTIVE: To explore the key components of CSP and their molecular targets and mechanisms in the treatment of FD. METHODS: Active compounds for CSP were identified from the TCMSP and SymMap databases, and the relevant targets were predicted. FD-related targets were obtained from the GeneCards and CTD database. In addition, using the protein-protein interactions (PPI) analysis, the common targets were obtained. Furthermore, the compound-target networks were created with Cytoscape. Finally, molecular docking was performed to identify the core targets and validate them experimentally. RESULTS: In total, 78 active compounds and 671 related targets of CSP were obtained. PPI network analysis identified 15 key FD-related compound targets. Molecular docking revealed that sitosterol and hyndarin exhibited good binding activities with AKT1 and IL6, respectively. Animal experiments have shown that CSP effectively increased the protein levels of AKT1 and reduced the serum levels of IL-6 in FD rats. CONCLUSION: This study provides a theoretical evidence for the analysis of the molecular targets and mechanisms of the action of CSP in FD.

miR-196a-5p Correlates with Chronic Atrophic Gastritis Progression to Gastric Cancer and Induces Malignant Biological Behaviors of Gastric Cancer Cells by Targeting ACER2.

BACKGROUND: As the prognosis of early gastric cancer (EGC) is significantly better than that of advanced gastric cancer (AGC), the development of biomarkers to monitor the progression of chronic atrophic gastritis (CAG) to gastric cancer (GC) is essential. METHODS: Stomach tissue miRNA and mRNA sequences from patients with chronic non-atrophic gastritis (CNAG), CAG, precancerous lesions of gastric cancer (PLGC), and GC were analyzed. A publicly available GC-related miRNA microarray dataset was obtained from the Gene Expression Omnibus database. Spearman's correlation and differential gene analyses, and clinical validation were used to identify novel miRNAs correlating with CAG progression to GC. miRNA targets were predicted using weighted gene co-expression analysis and databases. A dual-luciferase reporter assay was performed to check for direct interaction between miR-196a-5p and ACER2. The CCK-8 and wound healing assays, and flow cytometry were performed to evaluate cell proliferation, migration, and apoptosis. RESULTS: miR-196a-5p was correlated with CAG progression to GC. Overexpression of miR-196a-5p promoted GC cell proliferation and migration and inhibited apoptosis, whereas suppression of miR-196a-5p exerted the opposite effect. Based on the prediction and luciferase assays, ACER2 was identified as the target of miR-196a-5p. ACER2 was downregulated in GC cell lines. Knockdown of ACER2 increased GC cell proliferation rates and migration ability and inhibited apoptosis, while ACER2 overexpression led to the opposite effect. CONCLUSIONS: miR-196a-5p correlated with CAG progression to GC and induced malignant biological behaviors of GC cells by targeting ACER2, providing a novel monitoring biomarker and target for GC prevention.

Hesperidin promotes gastric motility in rats with functional dyspepsia by regulating Drp1-mediated ICC mitophagy.

Hesperidin is one of the main active ingredients of Citrus aurantium L. (Rutaceae) and tangerine peel, which have anti-inflammatory and antioxidant effects. In previous study, we found that gastric motility disorder in functional dyspepsia (FD) rats accompanied by excessive autophagy/mitochondrial swelling and even vacuolization in the interstitial cells of cajal (ICC), but the exact mechanism has not yet been investigated. Therefore, we used different doses of hesperidin (50 mg/kg, 100 mg/kg, and 200 mg/kg) to intervene in FD rats, and found that medium doses of hesperidin (100 mg/kg) significantly increased gastric motility in FD rats. Subsequently, FD rats were randomly divided into control group, model group, mdivi-1 group, mdivi-1+hesperidin group and hesperidin group, and mitochondrial division inhibitor (mdivi-1) was injected intraperitoneally to further investigate whether hesperidin could regulate dynamin-related protein 1 (Drp1)-mediated mitophagy in ICC to improve mitochondrial damage. The results showed that compared with the model group, the serum malondialdehyde (MDA) level decreased and the superoxide dismutase (SOD) level increased in the mdivi-1 and hesperidin groups (p < 0.001). Transmission electron microscopy (TEM) observed that the mitochondrial nuclear membrane was intact in gastric tissues with a clear internal cristae pattern, and autophagy lysosomes were rare. The co-localization expression of microtubule associated protein 1 light chain 3 (LC3) and voltage dependent anion channel 1 (VDAC1), Drp1 and translocase of the outer mitochondrial membrane 20 (Tom20) was significantly decreased (p < 0.001), the protein expression of mitochondrial Drp1, Beclin1 and LC3 were significantly decreased (p < 0.001), the protein expression of mitochondrial P62 and ckit in gastric tissue were significantly increased (p < 0.05, p < 0.001). The above situation was improved more significantly by the synergistic intervention of mdivi-1 and hesperidin. Therefore, hesperidin can improve mitochondrial damage and promote gastric motility in FD rats by regulating Drp1-mediated ICC mitophagy.

Design, Synthesis, and Anti-Breast Cancer Activity of Novel Fluorinated 7-O-Modified Genistein Derivatives.

BACKGROUND: Genistein has been limited in clinical application due to its low bioavailability, extremely poor liposolubility, and fast glycosylation rate, though it possesses anti-breast cancer activity. Therefore, the discovery of novel genistein derivatives is an urgency. OBJECTIVE: To enhance the anti-breast cancer activity of genistein, a series of novel fluorinated genistein derivatives were synthesized. METHODS: Their in vitro antitumor activity was investigated by the MTT assay against three cancer cell lines, via, MDA-MB-231, MCF-7, and MDA-MB-435, respectively. RESULTS: Analogs 1d, 2b, and 3b showed remarkable anticancer activities compared to tamoxifen, a clinical anti-breast cancer drug on the market. CONCLUSION: The activities against breast cancer of genistein were enhanced by introducing the 7- alkoxyl group and fluorine atom into the B-ring. Therefore, these compounds may be potential candidates for treating breast cancer.

A Two-Stage Method to Detect the Sex Ratio of Hemp Ducks Based on Object Detection and Classification Networks.

The sex ratio is an important factor affecting the economic benefits of duck groups in the process of hemp duck breeding. However, the current manual counting method is inefficient, and the results are not always accurate. On the one hand, ducks are in constant motion, and on the other hand, the manual counting method relies on manpower; thus, it is difficult to avoid repeated and missed counts. In response to these problems, there is an urgent need for an efficient and accurate way of calculating the sex ratio of ducks to promote the farming industry. Detecting the sex ratio of ducks requires accurate counting of male ducks and female ducks. We established the world's first manually marked sex classification dataset for hemp ducks, including 1663 images of duck groups; 17,090 images of whole, individual duck bodies; and 15,797 images of individual duck heads, which were manually captured and had sex information markers. Additionally, we used multiple deep neural network models for the target detection and sex classification of ducks. The average accuracy reached 98.68%, and with the combination of Yolov5 and VovNet_27slim, we achieved 99.29% accuracy, 98.60% F1 score, and 269.68 fps. The evaluation of the algorithm's performance indicates that the automation method proposed in this paper is feasible for the sex classification of ducks in the farm environment, and is thus a feasible tool for sex ratio estimation.

Ferroptosis Patterns Correlate with Immune Microenvironment Characterization in Gastric Cancer.

OBJECTIVE: We aimed to build a ferroptosis-based classifier to characterize the molecular features of gastric cancers (GC) and investigate the relationship between different ferroptosis patterns and GC tumor microenvironment (TME). METHODS: Based on the genomic and clinical information from TCGA portal and GEO database, non-negative matrix factorization (NMF) was used to identify ferroptosis subtypes in GC patients. In order to estimate the ferroptosis levels, we established ferroptosis subtype score (FSS) to quantify ferroptosis patterns and ferroptosis potential index (FPI) by principal component analysis (PCA). The correlations of different ferroptosis patterns with TME cell-infiltrating characteristics (including immune cell infiltration, immune checkpoints expression levels, tumor mutational burden (TMB) and immunotherapy response) were systematically analyzed. RESULTS: Two ferroptosis subtypes, C1 (with lower FSS) and C2 (with higher FSS), were determined. C2 displayed a significantly lower FPI than C1. Besides, C2 was associated with diffuse subtype while C1 with intestinal subtype. As for TME characteristics, C2 was in accordance with the immune-excluded phenotype as it showed more active immune and stromal activities but lower TMB, less probability of immunotherapy response and poorer prognosis. C1 was linked to immune-inflamed phenotype as it had lower stromal activities but increased neoantigen load, enhanced response to immunotherapy and relatively better prognosis. CONCLUSION: The systematic assessment of ferroptosis patterns and ferroptosis levels presented in our study implied that ferroptosis serves as an important factor in the formation of TME, which may expand the understanding of TME and provide a novel perspective for the development of targeted immunotherapeutic strategies for GC patients.

CXCR4 is a Novel Biomarker Correlated With Malignant Transformation and Immune Infiltrates in Gastric Precancerous Lesions.

Background: As early gastric cancer (EGC) has a far better prognosis than advanced gastric cancer (GC), early diagnosis and treatment are essential. However, understanding the mechanism of the process from gastric precancerous lesion (GPL) becoming EGC has made little advances. Besides, biomarkers that can monitor the progression of GPL-to-GC are still much insufficient. Methods: Key gene modules associated with GPL progression to EGC were identified by integrating two GPL-related data sets, GSE55696 and GSE130823, using the WGCNA method. Combining with the TCGA-STAD cohort, hub genes were identified. Immunofluorescence was conducted to validate the expression. To explore the implication of hub genes in GPL malignant transformation, a correlation test was conducted to identify their co-expression genes, co-expression cytokines, and co-expression immune cells. Least absolute shrinkage and selection operator (LASSO) Cox regression was applied to shrink CXCR4-related predictors and construct a prognostic model. Functional enrichment was applied for exploring the potential mechanism. Results: The green module in GSE55696 and the yellow module in GSE130823 were regarded as key gene modules associated with GPL progression to EGC, and 219 intersection genes from them were mainly enriched in critical immune biological processes. Combining with the TCGA-STAD cohort, CXCR4 was identified as a novel biomarker correlated with the malignant transformation of GPL, the positive rate of which was increased with GPL progression according to immunofluorescence. CXCR4 co-expression genes were found mainly involved in regulation of actin. CXCR4 co-expression cytokines were enriched in regulation of chemotaxis, cell chemotaxis, mononuclear cell migration, leukocyte chemotaxis, etc. As for co-expression immune cells, the expression level of CXCR4 was positively correlated with the abundance of macrophages but negatively correlated with that of effector memory T cells and NKT cells during GPL malignant transformation. In addition, the CXCR4-related prognostic model was able to predict the prognosis of GC and serve as an independent predictor for overall survival (OS). Conclusions: CXCR4 was a novel biomarker correlated with malignant transformation of GPL and played a vital role in the control of tumor immunity. CXCR4 is possible to serve as a therapeutic target for malignant transformation of GPL.

MBFFNet: Multi-Branch Feature Fusion Network for Colonoscopy.

Colonoscopy is currently one of the main methods for the detection of rectal polyps, rectal cancer, and other diseases. With the rapid development of computer vision, deep learning-based semantic segmentation methods can be applied to the detection of medical lesions. However, it is challenging for current methods to detect polyps with high accuracy and real-time performance. To solve this problem, we propose a multi-branch feature fusion network (MBFFNet), which is an accurate real-time segmentation method for detecting colonoscopy. First, we use UNet as the basis of our model architecture and adopt stepwise sampling with channel multiplication to integrate features, which decreases the number of flops caused by stacking channels in UNet. Second, to improve model accuracy, we extract features from multiple layers and resize feature maps to the same size in different ways, such as up-sampling and pooling, to supplement information lost in multiplication-based up-sampling. Based on mIOU and Dice loss with cross entropy (CE), we conduct experiments in both CPU and GPU environments to verify the effectiveness of our model. The experimental results show that our proposed MBFFNet is superior to the selected baselines in terms of accuracy, model size, and flops. mIOU, F score, and Dice loss with CE reached 0.8952, 0.9450, and 0.1602, respectively, which were better than those of UNet, UNet++, and other networks. Compared with UNet, the flop count decreased by 73.2%, and the number of participants also decreased. The actual segmentation effect of MBFFNet is only lower than that of PraNet, the number of parameters is 78.27% of that of PraNet, and the flop count is 0.23% that of PraNet. In addition, experiments on other types of medical tasks show that MBFFNet has good potential for general application in medical image segmentation.

Corrigendum: Current Evidence and Future Perspective of Accuracy of Artificial Intelligence Application for Early Gastric Cancer Diagnosis With Endoscopy: A Systematic and Meta-Analysis.

[This corrects the article DOI: 10.3389/fmed.2021.629080.].

Current Evidence and Future Perspective of Accuracy of Artificial Intelligence Application for Early Gastric Cancer Diagnosis With Endoscopy: A Systematic and Meta-Analysis.

Background & Aims: Gastric cancer is the common malignancies from cancer worldwide. Endoscopy is currently the most effective method to detect early gastric cancer (EGC). However, endoscopy is not infallible and EGC can be missed during endoscopy. Artificial intelligence (AI)-assisted endoscopic diagnosis is a recent hot spot of research. We aimed to quantify the diagnostic value of AI-assisted endoscopy in diagnosing EGC. Method: The PubMed, MEDLINE, Embase and the Cochrane Library Databases were searched for articles on AI-assisted endoscopy application in EGC diagnosis. The pooled sensitivity, specificity, and area under the curve (AUC) were calculated, and the endoscopists' diagnostic value was evaluated for comparison. The subgroup was set according to endoscopy modality, and number of training images. A funnel plot was delineated to estimate the publication bias. Result: 16 studies were included in this study. We indicated that the application of AI in endoscopic detection of EGC achieved an AUC of 0.96 (95% CI, 0.94-0.97), a sensitivity of 86% (95% CI, 77-92%), and a specificity of 93% (95% CI, 89-96%). In AI-assisted EGC depth diagnosis, the AUC was 0.82(95% CI, 0.78-0.85), and the pooled sensitivity and specificity was 0.72(95% CI, 0.58-0.82) and 0.79(95% CI, 0.56-0.92). The funnel plot showed no publication bias. Conclusion: The AI applications for EGC diagnosis seemed to be more accurate than the endoscopists. AI assisted EGC diagnosis was more accurate than experts. More prospective studies are needed to make AI-aided EGC diagnosis universal in clinical practice.

Pleural Effusion Is Associated with Severe Renal Dysfunction in Patients with Acute Pancreatitis.

BACKGROUND Renal dysfunction is a leading cause of death in patients with acute pancreatitis (AP) and often occurs later than respiratory complications. Whether respiratory complications can predict renal impairment remains unclear. The aim of this study was to investigate the association between pleural effusion and renal dysfunction in AP. MATERIAL AND METHODS Medical records were reviewed from individuals who were hospitalized with AP from January 1, 2015 to December 31, 2019. The patients were divided into 2 groups, based on the presence or absence of pleural effusion on admission. Disease severity, renal function parameters, and outcomes were compared between the 2 groups. RESULTS A total of 222 patients were enrolled, 25 of whom had pleural effusion on admission and 197 who did not. Patients with AP who had pleural effusion had more serious illness (higher incidences of pancreatic inflammation, pancreatic fluid collection, and moderate-to-severe AP; worse Bedside Index for Severity in Acute Pancreatitis score; and a higher modified computed tomography severity index [all P<0.05]) plus worse outcomes (higher incidences of ventilation and vasopressor use [both P<0.05]). Moreover, patients with pleural effusion had a higher level of blood urea nitrogen and lower estimated glomerular filtration rate (both P<0.05). After adjustment for potential confounders, pleural effusion was a risk factor for renal failure in patients with AP (odds ratio 6.32, 95% confidence interval 1.08-36.78, P=0.040). CONCLUSIONS Pleural effusion is associated with severe renal dysfunction in AP. Therefore, efforts should be made to improve early recognition and timely treatment of renal failure by closely monitoring renal function in patients with AP and pleural effusion on admission.

Construction and Validation of a Ferroptosis-Related Prognostic Model for Gastric Cancer.

BACKGROUND: Gastric cancer (GC), an extremely aggressive tumor with a very different prognosis, is the third leading cause of cancer-related mortality. We aimed to construct a ferroptosis-related prognostic model that can be distinguished prognostically. METHODS: The gene expression and the clinical data of GC patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus database (GEO). The ferroptosis-related genes were obtained from the FerrDb. Using the "limma" R package and univariate Cox analysis, ferroptosis-related genes with differential expression and prognostic value were identified in the TCGA cohort. Last absolute shrinkage and selection operator (LASSO) Cox regression was applied to shrink ferroptosis-related predictors and construct a prognostic model. Functional enrichment, ESTIMATE algorithm, and single-sample gene set enrichment analysis (ssGSEA) were applied for exploring the potential mechanism. GC patients from the GEO cohort were used for validation. RESULTS: An 8-gene prognostic model was constructed and stratified GC patients from TCGA and meta-GEO cohort into high-risk groups or low-risk groups. GC patients in high-risk groups have significantly poorer OS compared with those in low-risk groups. The risk score was identified as an independent predictor for OS. Functional analysis revealed that the risk score was mainly associated with the biological function of extracellular matrix (ECM) organization and tumor immunity. CONCLUSION: In conclusion, the ferroptosis-related model can be utilized for the clinical prognostic prediction in GC.

PlaneNet: an efficient local feature extraction network.

Due to memory and computing resources limitations, deploying convolutional neural networks on embedded and mobile devices is challenging. However, the redundant use of the 1 × 1 convolution in traditional light-weight networks, such as MobileNetV1, has increased the computing time. By utilizing the 1 × 1 convolution that plays a vital role in extracting local features more effectively, a new lightweight network, named PlaneNet, is introduced. PlaneNet can improve the accuracy and reduce the numbers of parameters and multiply-accumulate operations (Madds). Our model is evaluated on classification and semantic segmentation tasks. In the classification tasks, the CIFAR-10, Caltech-101, and ImageNet2012 datasets are used. In the semantic segmentation task, PlaneNet is tested on the VOC2012 datasets. The experimental results demonstrate that PlaneNet (74.48%) can obtain higher accuracy than MobileNetV3-Large (73.99%) and GhostNet (72.87%) and achieves state-of-the-art performance with fewer network parameters in both tasks. In addition, compared with the existing models, it has reached the practical application level on mobile devices. The code of PlaneNet on GitHub: https://github.com/LinB203/planenet.

Construction and validation of a TP53-associated immune prognostic model for gastric cancer.

Increasing evidence indicates that TP53 mutation impacts the patients' prognosis by regulating the gastric cancer (GC) immunophenotype. An immune prognostic signature (IPS) was constructed based on TP53 status. The effects of the IPS on the immune microenvironment of GC were analyzed. We also constructed a nomogram integrating the IPS and other clinical factors. An IPS was constructed in the TCGA cohort and validated in the meta-GEO cohort. TP53 mutation resulted in the downregulation of the immune response in GC. Concretely, high-risk patients were characterized by increased monocyte, macrophage M0 and T cell follicular helper infiltration; increased stromal score, ESTIMATE score and immune score; higher TIM3 and BTLA expression; and decreased dendritic cell and T cell CD4 memory-activated infiltration and tumor purity. The nomogram also showed good predictive performance. These results suggest that the IPS is an effective prognostic indicator for GC patients, which might provide a theoretical foundation for immunotherapy.

A novel ceRNA axis involves in regulating immune infiltrates and macrophage polarization in gastric cancer.

BACKGROUND: Increasing evidence suggests that the lncRNA-miRNA-mRNA regulatory network is highly correlated with gastric cancer (GC) development. However, a prognosis-associated lncRNA-miRNA-mRNA network remains to be identified in GC. METHODS: Differentially expressed genes (DEGs) were screened by integrating 6 microarray datasets using the RRA method. Hub genes were identified by analysing their degrees in a PPI (protein-protein interaction) network. Upstream miRNAs and lncRNAs of hub genes were predicted by miRTarBase and miRNet, respectively. Key genes, miRNAs and lncRNAs were identified by evaluating their expression and prognosis in GEPIA and Kaplan-Meier plotter, respectively. A key lncRNA-miRNA-mRNA network was constructed in Cytoscape, and the correlations were analysed in the ENCORI database. We also evaluated the mRNA expression of ceRNA axes in the TIMER and Oncomine databases and their correlation with prognosis in GC patients with different clinical features using Kaplan-Meier plotter. In addition, correlations between mRNA and immune infiltrating cells in GC were investigated by the TIMER database. Finally, several experiments were conducted to verify our analyses. RESULTS: Forty-two upregulated and 86 downregulated DEGs were obtained from the "RRA" integrated analysis. Eight of the 20 hub genes were identified as key genes by analysing their expression and prognosis. Seventeen miRNAs were predicted to target key genes, and low expression of 4 miRNAs suggested poor outcome in GC. Furthermore, 155 lncRNAs were predicted to target 4 key miRNAs, and only 5 lncRNAs were highly expressed, suggesting poor outcomes in patients with GC. Then, the H19-miR-29a-3p-COL1A2 axis was constructed by correlation analysis. In addition, COL1A2 was positively correlated with lymphatic metastasis, immune infiltrating cell levels, markers of monocytes, tumour-associated macrophages (TAMs), and M2 macrophages but not M1 macrophages in GC. The experimental results revealed that the H19-miR-29a-3p-COL1A2 axis may promote macrophage polarization from M1 to M2 in GC. CONCLUSIONS: A novel lncRNA-miRNA-mRNA axis was identified and may be involved in regulating immune cell infiltration and macrophage polarization, which may provide new treatment strategies for GC.

Construction of a 13-microRNA-based signature and prognostic nomogram for predicting overall survival in patients with hepatocellular carcinoma.

AIM: Hepatocellular carcinoma (HCC) is a common malignancy associated with a poor prognosis due to difficulties in reliably estimating overall survival (OS). MicroRNAs (miRNAs) play critical roles in HCC initiation, progression, and metastasis and are highly correlated with patient prognosis. Thus, miRNA-based risk signatures and nomograms are urgently required for predicting OS in patients with HCC. METHODS: We constructed a 13-miRNA-based signature and prognostic nomogram using 408 HCC samples and 58 normal tissues with miRNA sequencing data and clinical data from 323 patients downloaded from The Cancer Genome Atlas. A total of 195 patients were assigned as the internal validation cohort for verification and testing. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis was applied to investigate pathway enrichment for the signature. RESULTS: We identified and validated a 13-miRNA risk signature highly associating with the OS of HCC patients. The signature showed good performances by calculating C-index, area under the curve, and calibration curves. After verification and testing using an internal validation cohort, the results yielded a miRNA-based signature and a prognostic nomogram with reliable predictive accuracy. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis indicated that various genes and multiple pathways were closely related to the mechanisms of HCC proliferation and metastasis. CONCLUSION: We successfully identified a 13-miRNA-based signature and prognostic nomogram that are capable of predicting OS in patients with HCC.

Diagnostic value of MRI combined with ultrasound for lymph node metastasis in breast cancer: Protocol for a meta-analysis.

BACKGROUND: Early diagnosis and treatment of breast cancer are important to prevent fatal tumor progression. Axillary lymph node (ALN) status is the most significant prognostic factor for diagnosing overall survival in breast cancer patients. Axillary lymph node dissection (ALND) is regarded as the reference standard for determining ALN status. However, ALND is an invasive therapy with high morbidity and complications such as lymphedema, seroma and nerve injury. Comparatively, magnetic resonance imaging (MRI) and ultrasound are noninvasive and non-radiative techniques that are common imaging methods to diagnose breast cancer lymph node metastasis. Many studies have investigated the diagnostic value of MRI combined with ultrasound for breast cancer ALN metastasis, but the evidence has been insufficient to apply these modalities when diagnosing new patients. METHODS: We will search electronic databases including PubMed, EMbase, The Cochrane Library, Chinese Biomedical Database, WangFang Database, and China National Knowledge Infrastructure. The language of studies is limited in English or Chinese. The final search includes articles published in June, 2018. Stata 14.0 software will be used for all statistical analyses, and Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) will be utilized to evaluate the quality of the included studies. Meta-regression and subgroup analyses will be performed to explore heterogeneity, which will be derived from the different countries of origin of the included studies. Deeks' funnel plot asymmetry test will be demonstrated the inexistence of publication bias. RESULT: This study will provide a rational synthesis of current evidences for magnetic resonance imaging combined with ultrasound for breast cancer. CONCLUSION: The conclusion of this study will provide evidence for the diagnostic value of MRI combined with ultrasound for lymph node metastasis in breast cancer. REGISTRATION: PROS-PERO CRD42019134474.