An NGS-based assay for accurate detection and quantification of immune gene expression in mouse tumor models.

Tumor microenvironment (TME) is a complex dynamic system with many tumor-interacting components including tumor-infiltrating leukocytes (TILs), cancer associated fibroblasts, blood vessels, and other stromal constituents. It intrinsically affects tumor development and pharmacology of oncology therapeutics, particularly immune-oncology (IO) treatments. Accurate measurement of TME is therefore of great importance for understanding the tumor immunity, identifying IO treatment mechanisms, developing predictive biomarkers, and ultimately, improving the treatment of cancer. Here, we introduce a mouse-IO NGS-based (NGSmIO) assay for accurately detecting and quantifying the mRNA expression of 1080 TME related genes in mouse tumor models. The NGSmIO panel was shown to be superior to the commonly used microarray approach by hosting 300 more relevant genes to better characterize various lineage of immune cells, exhibits improved mRNA and protein expression correlation to flow cytometry, shows stronger correlation with mRNA expression than RNAseq with 10x higher sequencing depth, and demonstrates higher sensitivity in measuring low-expressed genes. We describe two studies; firstly, detecting the pharmacodynamic change of interferon-γ expression levels upon anti-PD-1: anti-CD4 combination treatment in MC38 and Hepa 1-6 tumors; and secondly, benchmarking baseline TILs in 14 syngeneic tumors using transcript level expression of lineage specific genes, which demonstrate effective and robust applications of the NGSmIO panel.

Interleukin-21 receptor signaling promotes metabolic dysfunction-associated steatohepatitis-driven hepatocellular carcinoma by inducing immunosuppressive IgA+ B cells.

BACKGROUND: Dysregulation of immune surveillance is tightly linked to the development of metabolic dysfunction-associated steatohepatitis (MASH)-driven hepatocellular carcinoma (HCC); however, its underlying mechanisms remain unclear. Herein, we aimed to determine the role of interleukin-21 receptor (IL-21R) in MASH-driven HCC. METHODS: The clinical significance of IL-21R was assessed in human HCC specimens using immunohistochemistry staining. Furthermore, the expression of IL-21R in mice was assessed in the STAM model. Thereafter, two different MASH-driven HCC mouse models were applied between IL-21R-deficient mice and wild type controls to explore the role of IL-21R in MASH-driven HCC. To further elucidate the potential mechanisms by which IL-21R affected MASH-driven HCC, whole transcriptome sequencing, flow cytometry and adoptive lymphocyte transfer were performed. Finally, flow cytometry, enzyme-linked immunosorbent assay, immunofluorescent staining, chromatin immunoprecipitation assay and western blotting were conducted to explore the mechanism by which IL-21R induced IgA+ B cells. RESULTS: HCC patients with high IL-21R expression exhibited poor relapse-free survival, advanced TNM stage and severe steatosis. Additionally, IL-21R was demonstrated to be upregulated in mouse liver tumors. Particularly, ablation of IL-21R impeded MASH-driven hepatocarcinogenesis with dramatically reduction of lipid accumulation. Moreover, cytotoxic CD8+ T lymphocyte activation was enhanced in the absence of IL-21R due to the reduction of immunosuppressive IgA+ B cells. Mechanistically, the IL-21R-STAT1-c-Jun/c-Fos regulatory axis was activated in MASH-driven HCC and thus promoted the transcription of Igha, resulting in the induction of IgA+ B cells. CONCLUSIONS: IL-21R plays a cancer-promoting role by inducing IgA+ B cells in MASH-driven hepatocarcinogenesis. Targeting IL-21R signaling represents a potential therapeutic strategy for cancer therapy.

Narazaciclib, a novel multi-kinase inhibitor with potent activity against CSF1R, FLT3 and CDK6, shows strong anti-AML activity in defined preclinical models.

CSF1R is a receptor tyrosine kinase responsible for the growth/survival/polarization of macrophages and overexpressed in some AML patients. We hypothesized that a novel multi-kinase inhibitor (TKi), narazaciclib (HX301/ON123300), with high potency against CSF1R (IC50 ~ 0.285 nM), would have anti-AML effects. We tested this by confirming HX301's high potency against CSF1R (IC50 ~ 0.285 nM), as well as other kinases, e.g. FLT3 (IC50 of ~ 19.77 nM) and CDK6 (0.53 nM). An in vitro proliferation assay showed that narazaciclib has a high growth inhibitory effect in cell cultures where CSF1R or mutant FLT3-ITD variants that may be proliferation drivers, including primary macrophages (IC50 of 72.5 nM) and a subset of AML lines (IC50 < 1.5 µM). In vivo pharmacology modeling of narazaciclib using five AML xenografts resulted in: inhibition of MV4-11 (FLT3-ITD) subcutaneous tumor growth and complete suppression of AM7577-PDX (FLT3-ITD/CSF1Rmed) systemic growth, likely due to the suppression of FLT3-ITD activity; complete suppression of AM8096-PDX (CSF1Rhi/wild-type FLT3) growth, likely due to the inhibition of CSF1R ("a putative driver"); and nonresponse of both AM5512-PDX and AM7407-PDX (wild-type FLT3/CSF1Rlo). Significant leukemia load reductions in bone marrow, where disease originated, were also achieved in both responders (AM7577/AM8096), implicating that HX301 might be a potentially more effective therapy than those only affecting peripheral leukemic cells. Altogether, narazaciclib can potentially be a candidate treatment for a subset of AML with CSF1Rhi and/or mutant FLT3-ITD variants, particularly second generation FLT3 inhibitor resistant variants.

ATG-101 Is a Tetravalent PD-L1×4-1BB Bispecific Antibody That Stimulates Antitumor Immunity through PD-L1 Blockade and PD-L1-Directed 4-1BB Activation.

Immune checkpoint inhibitors (ICI) have transformed cancer treatment. However, only a minority of patients achieve a profound response. Many patients are innately resistant while others acquire resistance to ICIs. Furthermore, hepatotoxicity and suboptimal efficacy have hampered the clinical development of agonists of 4-1BB, a promising immune-stimulating target. To effectively target 4-1BB and treat diseases resistant to ICIs, we engineered ATG-101, a tetravalent "2+2″ PD-L1×4-1BB bispecific antibody. ATG-101 bound PD-L1 and 4-1BB concurrently, with a greater affinity for PD-L1, and potently activated 4-1BB+ T cells when cross-linked with PD-L1-positive cells. ATG-101 activated exhausted T cells upon PD-L1 binding, indicating a possible role in reversing T-cell dysfunction. ATG-101 displayed potent antitumor activity in numerous in vivo tumor models, including those resistant or refractory to ICIs. ATG-101 greatly increased the proliferation of CD8+ T cells, the infiltration of effector memory T cells, and the ratio of CD8+ T/regulatory T cells in the tumor microenvironment (TME), rendering an immunologically "cold" tumor "hot." Comprehensive characterization of the TME after ATG-101 treatment using single-cell RNA sequencing further revealed an altered immune landscape that reflected increased antitumor immunity. ATG-101 was well tolerated and did not induce hepatotoxicity in non-human primates. According to computational semimechanistic pharmacology modeling, 4-1BB/ATG-101/PD-L1 trimer formation and PD-L1 receptor occupancy were both maximized at around 2 mg/kg of ATG-101, providing guidance regarding the optimal biological dose for clinical trials. In summary, by localizing to PD-L1-rich microenvironments and activating 4-1BB+ immune cells in a PD-L1 cross-linking-dependent manner, ATG-101 safely inhibits growth of ICI resistant and refractory tumors. SIGNIFICANCE: The tetravalent PD-L1×4-1BB bispecific antibody ATG-101 activates 4-1BB+ T cells in a PD-L1 cross-linking-dependent manner, minimizing the hepatotoxicity of existing 4-1BB agonists and suppressing growth of ICI-resistant tumors. See related commentary by Ha et al., p. 1546.

Construction and validation of artificial intelligence pathomics models for predicting pathological staging in colorectal cancer: Using multimodal data and clinical variables.

OBJECTIVE: This retrospective observational study aims to develop and validate artificial intelligence (AI) pathomics models based on pathological Hematoxylin-Eosin (HE) slides and pathological immunohistochemistry (Ki67) slides for predicting the pathological staging of colorectal cancer. The goal is to enable AI-assisted accurate pathological staging, supporting healthcare professionals in making efficient and precise staging assessments. METHODS: This study included a total of 267 colorectal cancer patients (training cohort: n = 213; testing cohort: n = 54). Logistic regression algorithms were used to construct the models. The HE image features were used to build the HE model, the Ki67 image features were used for the Ki67 model, and the combined model included features from both the HE and Ki67 images, as well as tumor markers (CEA, CA724, CA125, and CA242). The predictive results of the HE model, Ki67 model, and tumor markers were visualized through a nomogram. The models were evaluated using ROC curve analysis, and their clinical value was estimated using decision curve analysis (DCA). RESULTS: A total of 260 deep learning features were extracted from HE or Ki67 images. The AUC for the HE model and Ki67 model in the training cohort was 0.885 and 0.890, and in the testing cohort, it was 0.703 and 0.767, respectively. The combined model and nomogram in the training cohort had AUC values of 0.907 and 0.926, and in the testing cohort, they had AUC values of 0.814 and 0.817. In clinical DCA, the net benefit of the Ki67 model was superior to the HE model. The combined model and nomogram showed significantly higher net benefits compared to the individual HE model or Ki67 model. CONCLUSION: The combined model and nomogram, which integrate pathomics multi-modal data and clinical-pathological variables, demonstrated superior performance in distinguishing between Stage I-II and Stage III colorectal cancer. This provides valuable support for clinical decision-making and may improve treatment strategies and patient prognosis. Furthermore, the use of immunohistochemistry (Ki67) slides for pathomics modeling outperformed HE slide, offering new insights for future pathomics research.

Skeletal Editing of Benzene Motif: Photopromoted Transannulation for Synthesis of DNA-Encoded Seven-Membered Rings.

In this report, we present a photopromoted, metal-free transannulation of phenyl azides for the synthesis of DNA-encoded seven-membered rings. The transformation is efficiently achieved through a skeletal editing strategy targeting the benzene motif coupled with a Reversible Adsorption to Solid Support (RASS) strategy. A variety of valuable DNA-encoded seven-membered ring compounds, including DNA-encoded 3H-azepines, azepinones, and unnatural amino acids, are now accessible. Crucially, this DNA-compatible protocol can also be applied for the introduction of complex molecules, as exemplified by Lorcaserin and Betahistine. The selective conversion of readily available phenyl rings into high-value seven-membered rings offers a promising avenue for the construction of diversified and drug-like DNA-encoded library.

Development and validation of a Radiopathomics model based on CT scans and whole slide images for discriminating between Stage I-II and Stage III gastric cancer.

OBJECTIVE: This study aimed to develop and validate an artificial intelligence radiopathological model using preoperative CT scans and postoperative hematoxylin and eosin (HE) stained slides to predict the pathological staging of gastric cancer (stage I-II and stage III). METHODS: This study included a total of 202 gastric cancer patients with confirmed pathological staging (training cohort: n = 141; validation cohort: n = 61). Pathological histological features were extracted from HE slides, and pathological models were constructed using logistic regression (LR), support vector machine (SVM), and NaiveBayes. The optimal pathological model was selected through receiver operating characteristic (ROC) curve analysis. Machine learnin algorithms were employed to construct radiomic models and radiopathological models using the optimal pathological model. Model performance was evaluated using ROC curve analysis, and clinical utility was estimated using decision curve analysis (DCA). RESULTS: A total of 311 pathological histological features were extracted from the HE images, including 101 Term Frequency-Inverse Document Frequency (TF-IDF) features and 210 deep learning features. A pathological model was constructed using 19 selected pathological features through dimension reduction, with the SVM model demonstrating superior predictive performance (AUC, training cohort: 0.949; validation cohort: 0.777). Radiomic features were constructed using 6 selected features from 1834 radiomic features extracted from CT scans via SVM machine algorithm. Simultaneously, a radiopathomics model was built using 17 non-zero coefficient features obtained through dimension reduction from a total of 2145 features (combining both radiomics and pathomics features). The best discriminative ability was observed in the SVM_radiopathomics model (AUC, training cohort: 0.953; validation cohort: 0.851), and clinical decision curve analysis (DCA) demonstrated excellent clinical utility. CONCLUSION: The radiopathomics model, combining pathological and radiomic features, exhibited superior performance in distinguishing between stage I-II and stage III gastric cancer. This study is based on the prediction of pathological staging using pathological tissue slides from surgical specimens after gastric cancer curative surgery and preoperative CT images, highlighting the feasibility of conducting research on pathological staging using pathological slides and CT images.

Spindle apparatus coiled-coil protein 1 (SPDL1) serves as a novel prognostic biomarker in triple-negative breast cancer.

BACKGROUND: Triple-negative breast cancer (TNBC) has a poor prognosis, an ineffective diagnosis, and a high degree of aggressiveness. Therefore, novel therapeutic targets for TNBC urgently need to be identified. METHODS: Through a series of bioinformatics analyses, including analysis of differential gene expression, protein-protein interaction (PPI) network, univariate cox regression, immune infiltration, pathway enrichment, etc, as well as auxiliary immunohistochemistry (IHC) and protein quantitativae analysis, to explore prognostic marker for TNBC. RESULTS: In TNBC tissues, we found that SPDL1 (CCDC99) was considerably overexpressed at both the mRNA and protein levels compared to that in normal and non-TNBC tissues. Additionally, we found that SPDL1-high expression was strongly linked to poor prognosis in TNBC patients. Excessive SPDL1 expression was positively correlated with tumor growth and strongly linked to the cell cycle, DNA replication, and the p53 signaling pathway. In addition, CIBERSORT analysis revealed that SPDL1 can affect the tumor immune microenvironment (TME) in TNBC, encourage the development of TNBC and act as a potential prognostic biomarker for TNBC. Patients with SPDL1-high expression were more sensitive to AZD8055. Notably, we discovered that SPDL1 is highly expressed in the majority of malignancies and may have an impact on the pancancer prognosis. CONCLUSIONS: SPDL1 can serve as a novel prognostic marker for TNBC and pancancer patients.

Diabetes mellitus and Alzheimer's disease: Vacuolar adenosine triphosphatase as a potential link.

Globally, the incidence of diabetes mellitus (DM) and Alzheimer's disease (AD) is increasing year by year, causing a huge economic and social burden, and their pathogenesis and aetiology have been proven to have a certain correlation. In recent years, more and more studies have shown that vacuolar adenosine triphosphatases (v-ATPases) in eukaryotes, which are biomolecules regulating lysosomal acidification and glycolipid metabolism, play a key role in DM and AD. This article describes the role of v-ATPase in DM and AD, including its role in glycolysis, insulin secretion and insulin resistance (IR), as well as its relationship with lysosomal acidification, autophagy and ß-amyloid (Aß). In DM, v-ATPase is involved in the regulation of glucose metabolism and IR. v-ATPase is closely related to glycolysis. On the one hand, v-ATPase affects the rate of glycolysis by affecting the secretion of insulin and changing the activities of key glycolytic enzymes hexokinase (HK) and phosphofructokinase 1 (PFK-1). On the other hand, glucose is the main regulator of this enzyme, and the assembly and activity of v-ATPase depend on glucose, and glucose depletion will lead to its decomposition and inactivation. In addition, v-ATPase can also regulate free fatty acids, thereby improving IR. In AD, v-ATPase can not only improve the abnormal brain energy metabolism by affecting lysosomal acidification and autophagy but also change the deposition of Aß by affecting the production and degradation of Aß. Therefore, v-ATPase may be the bridge between DM and AD.

A comprehensive radiopathological nomogram for the prediction of pathological staging in gastric cancer using CT-derived and WSI-based features.

OBJECTIVE: This study aims to develop and validate an innovative radiopathomics model that combines radiomics and pathomics features to effectively differentiate between stages I-II and stage III gastric cancer (pathological staging). METHODS: Our study included 200 patients with well-defined stages of gastric cancer divided into a training cohort (n = 140) and a test cohort (n = 60). Radiomics features were extracted from contrast-enhanced CT images using PyRadiomics, while pathomics features were obtained from whole slide images of pathological specimens through a fine-tuned deep learning model (ResNet-18). After rigorous feature dimensionality reduction and selection, we constructed radiomics models (SVM_rad, LR_rad, and MLP_rad) and pathomics models (SVM_path, LR_path, and MLP_path) utilizing support vector machine (SVM), logistic regression (LR), and multilayer perceptron (MLP) algorithms. The optimal radiomics and pathomics models were chosen based on comprehensive evaluation criteria such as ROC curves, Hosmer‒Lemeshow tests, and calibration curve tests. Feature patterns extracted from the best-performing radiomics model (MLP_rad) and pathomics model (SVM_rad) were integrated to create a powerful radiopathomics nomogram. RESULTS: From a pool of 1834 radiomics features extracted from CT images, 14 were selected to construct radiomics models. Among these, the MLP_rad model exhibited the most robust predictive performance (AUC, training cohort: 0.843; test cohort: 0.797). Likewise, 10 pathomics features were chosen from 512 extracted from whole slide images to build pathomics models, with the SVM_path model demonstrating the highest predictive efficiency (AUC, training cohort: 0.937; test cohort: 0.792). The combined radiopathomics nomogram model exhibited optimal discriminative ability (AUC, training cohort: 0.951; test cohort: 0.837), as confirmed by decision curve analysis (DCA), which indicated superior clinical effectiveness. CONCLUSION: This study presents a cutting-edge radiopathomics nomogram model designed to predict pathological staging in gastric cancer, distinguishing between stages I-II and stage III. Our research leverages preoperative CT images and histopathological slides to forecast gastric cancer staging accurately, potentially facilitating the estimation of staging before radical gastric cancer surgery in the future.

Endogenous H2O2 Self-Replenishment and Sustainable Cascades Enhance the Efficacy of Sonodynamic Therapy.

Purpose: Sonodynamic therapy (SDT), with its high tissue penetration and noninvasive advantages, represents an emerging approach to eradicating solid tumors. However, the outcomes of SDT are typically hampered by the low oxygen content and immunosuppression in the tumor microenvironment (TME). Accordingly, we constructed a cascade nanoplatform to regulate the TME and improve the anti-tumor efficiency of SDT. Methods: In this study, we rationally design cascade nanoplatform by incorporating immunostimulant hyaluronic acid (HA) and sonosensitizer chlorin e6 (Ce6) on the polydopamine nanocarrier that is pre-doped with platinum nanozymes (designated Ce6/Pt@PDA-HA, PPCH). Results: The cascade reactions of PPCH are evidenced by the results that HA exhibits reversing immunosuppressive that converts M2 macrophages into M1 macrophages in situ, while producing H2O2, and then platinum nanozymes further catalyze the H2O2 to produce O2, and O2 produces abundant singlet oxygen (1O2) under the action of Ce6 and low-intensity focused ultrasound (LIFU), resulting in a domino effect and further amplifying the efficacy of SDT. Due to its pH responsiveness and mitochondrial targeting, PPCH effectively accumulates in tumor cells. Under LIFU irradiation, PPCH effectively reverses immunosuppression, alleviates hypoxia in the TME, enhances reactive oxygen species (ROS) generation, and enhances SDT efficacy for eliminating tumor cells in vivo and in vitro. Meanwhile, an in vivo dual-modal imaging including fluorescence and photoacoustic imaging achieves precise tumor diagnosis. Conclusion: This cascade nanoplatform will provide a promising strategy for enhancing SDT eradication against tumors by modulating immunosuppression and relieving hypoxia.

Long non-coding RNA NRSN2-AS1 promotes ovarian cancer progression through targeting PTK2/ß-catenin pathway.

As a common malignant tumor among women, ovarian cancer poses a serious threat to their health. This study demonstrates that long non-coding RNA NRSN2-AS1 is over-expressed in ovarian cancer tissues using patient sample and tissue microarrays. In addition, NRSN2-AS1 is shown to promote ovarian cancer cell proliferation and metastasis both in vitro and in vivo. Mechanistically, NRSN2-AS1 stabilizes protein tyrosine kinase 2 (PTK2) to activate the ß-catenin pathway via repressing MG-53-mediated ubiquitinated degradation of PTK2, thereby facilitating ovarian cancer progression. Rescue experiments verify the function of the NRSN2-AS1/PTK2/ß-catenin axis and the effects of MG53 on this axis in ovarian cancer cells. In conclusion, this study demonstrates the key role of the NRSN2-AS1/PTK2/ß-catenin axis for the first time and explores its potential clinical applications in ovarian cancer.

Clinicopathological features and prognostic significance of pulmonary adenocarcinoma with signet ring cell components: meta-analysis and SEER analysis.

Pulmonary adenocarcinoma is a common type of lung cancer that has been on the rise in recent years. Signet ring cell components (SRCC) can be present in various patterns of pulmonary adenocarcinoma, including papillary, acinar, and solid patterns. "Signet ring cell carcinoma" is a distinct subtype in the 2014 WHO classification of lung neoplasms, subsequent WHO classifications in 2015 and 2021 have deemed signet ring cells as accompanying morphological features with no clinical significance. The prognostic and clinical implications of SRCC in pulmonary adenocarcinoma remain controversial. Therefore, we conducted a meta-analysis to investigate the clinicopathological features and prognostic factors of SRCC in pulmonary adenocarcinoma. We conducted a comprehensive search in PubMed, EMBASE, and Web of Science to identify studies that examined the clinicopathological features and prognostic implications of pulmonary adenocarcinoma with SRCC. We used both fixed- and random-effects models to analyze the data and calculate the pooled hazard ratio (HR) and odds ratio (OR) with 95% confidence intervals (CIs). Additionally, we explored the prognostic significance of SRCC in pulmonary adenocarcinoma using the Surveillance, Epidemiology, and End Results (SEER) database. Our meta-analysis included 29 studies with pulmonary adenocarcinoma and SRCC components. The results showed that pulmonary adenocarcinoma with SRCC was associated with larger tumor size (OR = 1.99; 95% CI, 1.62-2.44, p < 0.001), advanced overall stage (OR = 5.18, 95% CI, 3.28-8.17, p < 0.00001) and lymph node stage (OR = 5.79, 95% CI, 1.96-17.09, p = 0.001), and worse overall survival (OS) compared to those without SRCC (HR = 1.80, 95% CI, 1.50-2.16, p < 0.00001). Analysis using the SEER dataset confirmed these findings. Our meta-analysis provides evidence that pulmonary adenocarcinoma with SRCC is associated with distinct clinicopathological features and a poorer prognosis. These findings have important implications for the management and treatment of patients. However, further studies are needed to validate these findings and explore the significance of SRCC in various subtypes of pulmonary adenocarcinoma.

Characterization of CircRNA-Associated CeRNA Networks in Folate Deficiency-Induced Neural Tube Defects.

Objective: Circular RNAs (circRNAs) participate in several important pathological processes and have been used in the diagnosis and treatment of various diseases. This study aimed to investigate the role of circRNAs in neural tube defects (NTDs). Method: We characterized circRNA-associated competitive endogenous RNA (ceRNA) networks in brain tissue of low folate -induced NTDs mouse at embryonic day 13.5 by high-throughput sequencing. The expression levels of Circzfp644, miR-20-5p and Gas7 were detected by RT-PCR. Gas7 and Circzfp644 functions were determined by miRNA-mimics and inhibitors in mouse teratocarcinoma cells (F9 cells), and luciferase gene reporter assay was assessed in the F9 cells. In addition, the expression levels of Circzfp644, miR-20-5p and Gas7 were determined by Nanostring in human NTDs tissues. Results: We detected 57 circRNA transcripts, 16 miRNAs, and 148 mRNAs that were significantly dysregulated in NTDs brain tissues compared with their expression levels in control (normal) tissues. Circzfp644 shared miRNA response elements with the growth arrest specific 7 ( Gas7) gene and competitively bound with miR-20-5p to increase the expression of Gas7. Downregulation of Circzfp644 and Gas7 and upregulation of miR-20-5p were found in human NTD tissue. Conclusion: This study provides new perspectives on the role of circRNAs in nervous system development and the pathogenesis of NTDs.

Natural products modulate NLRP3 in ulcerative colitis.

Ulcerative colitis (UC) is a clinically common, progressive, devastating, chronic inflammatory disease of the intestine that is recurrent and difficult to treat. Nod-like receptor protein 3 (NLRP3) is a protein complex composed of multiple proteins whose formation activates cysteine aspartate protease-1 (caspase-1) to induce the maturation and secretion of inflammatory mediators such as interleukin (IL)-1ß and IL-18, promoting the development of inflammatory responses. Recent studies have shown that NLRP3 is associated with UC susceptibility, and that it maintains a stable intestinal environment by responding to a wide range of pathogenic microorganisms. The mainstay of treatment for UC is to control inflammation and relieve symptoms. Despite a certain curative effect, there are problems such as easy recurrence after drug withdrawal and many side effects associated with long-term medication. NLRP3 serves as a core link in the inflammatory response. If the relationship between NLRP3 and gut microbes and inflammation-associated factors can be analyzed concerning its related inflammatory signaling pathways, its expression status as well as specific mechanism in the course of IBD can be elucidated and further considered for clinical diagnosis and treatment of IBD, it is expected that the development of lead compounds targeting the NLRP3 inflammasome can be developed for the treatment of IBD. Research into the prevention and treatment of UC, which has become a hotbed of research in recent years, has shown that natural products are rich in therapeutic means, and multi-targets, with fewer adverse effects. Natural products have shown promise in treating UC in numerous basic and clinical trials over the past few years. This paper describes the regulatory role of the NLRP3 inflammasome in UC and the mechanism of recent natural products targeting NLRP3 against UC, which provides a reference for the clinical treatment of this disease.

Identification of immunity-related lncRNAs and construction of a ceRNA network of potential prognostic biomarkers in acute myeloid leukemia.

Objective: Using bioinformatics analyses, this study aimed to identify lncRNAs related to the immune status of acute myeloid leukemia (AML) patients and ascertain the potential impact in immunity-related competing endogenous RNA (ceRNA) networks on AML prognosis. Methods: AML-related RNA-seq FPKM data, AML-related miRNA expression microarray data, and gene sets associated with immunity-related pathways were, respectively, obtained from the TCGA, GEO, and ImmReg databases. An immunity-related ceRNA network was then constructed according to the predicted interactions between AML-related mRNAs, lncRNAs, and miRNAs. After performing LASSO and multivariate Cox regression analyses, lncRNAs in the ceRNA network were used to establish an AML prognostic model. According to mutual regulatory relationships and consistent trends of expression among candidate ceRNAs, two ceRNA subnetworks related to the AML prognostic model were determined. Finally, the correlation between the expression levels of mRNAs, lncRNAs, and miRNAs in each ceRNA subnetwork and immune cell infiltration (assessed by combining the ESTIMATE and CIBERSORT methods and ssGSEA) was analyzed. Results: A total of 424 immunity-related differentially expressed (IR-DE) mRNAs (IR-DEmRNAs), 191 IR-DElncRNAs, and 69 IR-DEmiRNAs were obtained, and a ceRNA network of 20 IR-DElncRNAs, 6 IR-DEmRNAs, and 3 IR-DEmiRNAs was established. Univariate Cox regression analysis was conducted on 20 IR-DElncRNAs, and 7 of these were identified to be significantly correlated with the overall survival (OS) time in AML patients. Then, two IR-DElncRNAs (MEG3 and HCP5) were screened as independent OS-related factors by LASSO and multivariable Cox regression analyses, and a prognostic model was constructed to evaluate the survival risk in AML patients. Survival analyses indicated that the OS of patients was often poor in the high-risk group. Additionally, from this model, two ceRNA regulatory pathways, namely, MEG3/miR-125a-5p/SEMA4C and HCP5/miR-125b-5p/IL6R, which were potentially involved in the immune regulation of AML prognosis were identified. Conclusion: lncRNAs HCP5 and MEG3 may act as key ceRNAs in the pathogenesis in AML by regulating immune cell representation as part of the regulatory lncRNA-miRNA-mRNA axes. The candidate mRNAs, lncRNAs, and miRNAs included in the ceRNA network identified here may serve as useful prognostic biomarkers and immunotherapeutic targets for AML.

The role and mechanism of flavonoid herbal natural products in ulcerative colitis.

Ulcerative colitis (UC) is a chronic inflammatory disease of the intestine that presents clinically with abdominal pain, mucopurulent stools, and posterior urgency. The lesions of UC are mainly concentrated in the rectal and colonic mucosa and submucosa. For patients with mild to moderate UC, the best pharmacological treatment includes glucocorticoids, immunosuppressants, antibiotics, and biologics, but the long-term application can have serious toxic side effects. Currently, nearly 40% of UC patients are treated with herbal natural products in combination with traditional medications to reduce the incidence of toxic side effects. Flavonoid herbal natural products are the most widely distributed polyphenols in plants and fruits, which have certain antioxidant and anti-inflammatory activities. Flavonoid herbal natural products have achieved remarkable efficacy in the treatment of UC. The pharmacological mechanisms are related to anti-inflammation, promotion of mucosal healing, maintenance of intestinal immune homeostasis, and regulation of intestinal flora. In this paper, we summarize the flavonoid components of anti-ulcerative colitis and their mechanisms reported in the past 10 years, to provide a basis for rational clinical use and the development of new anti-ulcerative colitis drugs.

A rare rectal gastrointestinal stromal tumor with indolent biological behavior: A case study.

The overall incidence of rectal gastrointestinal stromal tumor (RGIST) has risen, but it remains a rare disease. Furthermore, tumor rupture is associated with poor prognosis. The present study reported a rare case of RGIST with indolent biological behavior. The biological behavior of this RGIST was analyzed and its malignant potential was evaluated using a guideline-based risk stratification assessment. The patient was diagnosed with a rectal tumor at the Third Affiliated Hospital of Qiqihar Medical University (Qiqihar, China) in April 2020 and a partial resection biopsy was then performed. This resection counts as a rupture. The biopsy confirmed RGIST and the patient refused further examination and treatment due to economic concerns. However, the patient survives with no tumor progression and metastasis until now, May 2022. In conclusion, based on the present case, tumor rupture in indolent RGIST is not necessarily associated with poor outcome.