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This review provides an overview of common assays used to screen for gene methylation and early biomarkers of methylation in various cancers. DNA methylation, one of the most well-studied epigenetic modifications, plays a crucial role in normal cell and tissue development. It is increasingly utilized as a biomarker for early cancer and precancerous lesion detection. In this review, we describe common methods associated with gene methylation, including bisulfite sequencing PCR (BSP), pyrosequencing technology (PYR), methylation-specific polymerase chain reaction (MS-PCR/MSP), methylation-sensitive high-resolution melting (MS-HRM), methylation sensitive single nucleotide primer extension (MS-SnuPE), Epityper, Droplet digital PCR (ddPCR), methylation-sensitive restriction enzyme (MSRE) analysis, COBRA and PacBio SMRT sequencing. Additionally, we summarize methylation markers and their sample types for early cancer screening, focusing on colorectal cancer, hepatocellular carcinoma, gastric cancer, pancreatic cancer, esophageal cancer (digestive system), lung cancer (respiratory system), breast cancer, ovarian cancer, cervical cancer (female reproductive system), bladder cancer, and prostate cancer (urinary system). Furthermore, we discuss the recent detection of methylation biomarkers in clinical samples such as blood, urine, sputum, feces, and tissues. The aim of this review is to summarize early methylation biomarkers that are expected or have already been clinically applied. For future large-scale studies or the integration of available methylome level data, the discovery of sufficiently sensitive clinical biomarkers is essential.

Objective: To explore the mechanism of Wenyang Shengji Ointment (温阳生肌膏, WYSJO) in the treatment of diabetic wounds from the perspective of network pharmacology, and to verify it by animal experiments. Methods: The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and related literature were used to screen active compounds in WYSJO and their corresponding targets. GeneCards, Online Mendelian Inheritance in Man (OMIM), DrugBank, PharmGkb, and Therapeutic Target Database (TTD) databases were employed to identify the targets associated with diabetic wounds. Cytoscape 3.9.0 was used to map the active ingredients in WYSJO, which was the diabetic wound target network. Search Tool for the Retrieval of Interaction Gene/Proteins (STRING) platform was utilized to construct protein-protein interaction (PPI) network. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were performed to identify signaling pathways between WYSJO and diabetic wounds. AutoDock 1.5.6 was used for molecular docking of core components in WYSJO to their targets. Eighteen rats were randomly divided into control, model, and WYSJO groups (n = 6). The model and WYSJO groups were used to prepare the model of refractory wounds in diabetes rats. The wound healing was observed on day 0, 5, 9, and 14 after treatment, and the wound tissue morphology was observed by hematoxylin-eosin (HE) staining. The expression levels of core genes were detected by quantitative real-time polymerase chain reaction (qPCR). Results: A total of 76 active compounds in WYSJO, 206 WYSJO drug targets, 3 797 diabetic wound targets, and 167 diabetic wound associated WYSJO targets were screened out through network pharmacology. With the use of WYSJO-diabetic wound target network, core targets of seven active compounds encompassing quercetin, daidzein, kaempferol, rhamnetin, rhamnocitrin, strictosamide, and diisobutyl phthalate (DIBP) in WYSJO were found. GO enrichment analysis showed that the treatment of diabetes wounds with WYSJO may involve lipopolysaccharide, bacteria-derived molecules, metal ions, foreign stimuli, chemical stress, nutrient level, hypoxia, and oxidative stress in the biological processes. KEGG enrichment analysis showed that the treatment of diabetes wounds with WYSJO may involve advanced glycation end products (AGE-RAGE), p53, interleukin (IL)-17, tumor necrosis factor (TNF), hypoxia inducible factor-1 (HIF-1), apoptosis, lipid, atherosclerosis, etc. The results of animal experiments showed that WYSJO could significantly accelerate the healing process of diabetic wounds (P < 0.05), alleviate inflammatory response, promote the growth of granulation tissues, and down-regulate the expression levels of eight core genes [histone crotonyltransferase p300 (EP300), protoc gene-oncogene c-Jun (JUN), myelocytomatosis (MYC), hypoxia inducible factor 1A (HIF1A), mitogen-activated protein kinase 14 (MAPK14), specificity protein 1 (SP1), tumor protein p53 (TP53), and estrogen receptor 1 (ESR1)] predicted by the network pharmacology (P < 0.05). Conclusion: The mechanism of WYSJO in treating diabetes wounds may be closely related to AGE-RAGE, p53, HIF-1, and other pathways. This study can provide new ideas for the pharmacological research of WYSJO, and provide a basis for its further transformation and application.

Abstract Background Liver metastasis of CRC is still the main cause of poor prognosis in patients with CRC. Previous studies have suggested that serpin family C member 1(SERPINC1) is involved in the development of a variety of tumours, but its effect on colorectal cancer progression has been poorly elucidated. Methods Based on the GEO database, this study identifies the core gene SERPINC1 associated with liver metastasis in CRC. We used transcriptomic data and immunohistochemical staining to explore the expression of SERPINC1 in normal, cancer, and liver metastases tissue from CRC patients. Clinical data obtained from our hospital were used to explore the impact of SERPINC1 on the prognosis of colon cancer patients. Mechanistically, the biological functions exerted by SERPINC1 in CRC were predicted by bioinformatics, and the results were validated by the results of the experiments in vitro. Cell lines with knockdown of SERPINC1 were performed a series assay such as trans well, CCK‐8 and colony formation assay to explore the relationship between SERPINC1 and proliferation and metastasis of CRC cells. Finally, the effect of SERPINC1 on the sensitivity of colon cancer patients to immune checkpoint therapy was evaluated. Results In CRC liver metastatic tissues, we found significantly high expression of SERPINC1. Briefly, 212 CRC cohorts showed that SERPINC1 was significantly associated with TNM stage and plasma CA19‐9 and CEA in CRC patients. Univariate and multivariate Cox demonstrated that SERPINC1 was significantly associated with 5‐year survival after radical surgery for colorectal cancer (p

Abstract Background Aberrant glycosylation, catalyzed by the specific glycosyltransferase, is one of the dominant features of cancers. Among the glycosyltransferase subfamilies, sialyltransferases (SiaTs) are an essential part which has close linkages with tumor-associated events, such as tumor growth, metastasis and angiogenesis. Considering the relationship between SiaTs and cancer, the current study attempted to establish an effective prognostic model with SiaTs-related genes (SRGs) to predict patients’ outcome and therapeutic responsiveness of bladder cancer. Methods RNA-seq data, clinical information and genomic mutation data were downloaded (TCGA-BLCA and GSE13507 datasets). The comprehensive landscape of the 20 SiaTs was analyzed, and the differentially expressed SiaTs-related genes were screened with “DESeq2” R package. ConsensusClusterPlus was applied for clustering, following with survival analysis with Kaplan–Meier curve. The overall survival related SRGs were determined with univariate Cox proportional hazards regression analysis, and the least absolute shrinkage and selection operator (LASSO) regression analysis was performed to generate a SRGs-related prognostic model. The predictive value was estimated with Kaplan–Meier plot and the receiver operating characteristic (ROC) curve, which was further validated with the constructed nomogram and decision curve. Results In bladder cancer tissues, 17 out of the 20 SiaTs were differentially expressed with CNV changes and somatic mutations. Two SiaTs_Clusters were determined based on the expression of the 20 SiaTs, and two gene_Clusters were identified based on the expression of differentially expressed genes between SiaTs_Clusters. The SRGs-related prognostic model was generated with 7 key genes (CD109, TEAD4, FN1, TM4SF1, CDCA7L, ATOH8 and GZMA), and the accuracy for outcome prediction was validated with ROC curve and a constructed nomogram. The SRGs-related prognostic signature could separate patients into high- and low-risk group, where the high-risk group showed poorer outcome, more abundant immune infiltration, and higher expression of immune checkpoint genes. In addition, the risk score derived from the SRGs-related prognostic model could be utilized as a predictor to evaluate the responsiveness of patients to the medical therapies. Conclusions The SRGs-related prognostic signature could potentially aid in the prediction of the survival outcome and therapy response for patients with bladder cancer, contributing to the development of personalized treatment and appropriate medical decisions.

In recent years, the poultry breeding industry has been converted into a large-scale, intensive, and intelligent production mode. The Internet of Things (IoT) is under rapid development, which promotes the development of precision livestock farming. In this study, we developed an intelligent service platform for a facility environment based on the IoT structure, utilizing the capabilities of Platform as a Service (PaaS). The platform consists of four layers, including an information perception layer, network layer, management service layer, and application layer. By using the cloud service model with a distributed network architecture, asynchronous data transmission, and a distributed file system, the platform can centrally manage multiple farm’s data. The intelligent service platform includes the following functions: displaying environmental data, water and electricity consumption, data analysis, and managing production data. Over a 500-day trial period in a live poultry house, the platform demonstrated high data integrity (>87%) and resilience against network disruptions and power outages. The data validity of each environmental element exceeded 94%, among which the validity of the temperature, humidity, and carbon dioxide concentration exceeded 99%. The overall accuracy of the dataset remained relatively high, providing a robust data foundation for further research. Key features included audio analysis, environmental monitoring, and production data management. The platform’s operational status was efficiently communicated via data statistics and email alerts, facilitating timely system recovery. The demonstrated modules included sound recognition, psychrometric charts for visual alerts, and financial analysis tools, offering versatile solutions for integrating PLF models and advanced analytics.

Low expression levels of breast cancer metastasis suppressor 1 like (BRMS1L) have been associated with the growth of cancer cells. However, the mechanisms underlying the role of BRMS1L as an antitumour transcription factor in the progression of NSCLC have not been explored. Herein, we reveal that BRMS1L plays a key role as a tumour suppressor in inhibiting NSCLC proliferation and metastasis. Mechanistically, BRMS1L overexpression results in the downregulation of glutathione peroxidase 2 (GPX2) expression and consequently causes abnormal glutathione metabolism and increased levels of reactive oxygen species (ROS) in cells, inducing oxidative stress injury and apoptosis. Furthermore, overexpression of GPX2 enhances the growth advantage and oxidative stress repair conferred by knockdown of BRMS1L. Importantly, we show that low expression of BRMS1L in NSCLC cells causes relatively high levels of antioxidant accumulation to maintain cell redox balance and renders cancer cells more sensitive to treatment with piperlongumine as an ROS inducer both in vitro and in vivo. These findings offer new insights into the role of BRMS1L as a transcriptional repressor in NSCLC and suggest that the BRMS1L expression level may be a potential biomarker for predicting the therapeutic response to small molecule ROS inducers, providing new ideas for targeted therapy.

Abstract Background and Objectives Anastomotic leakage is a serious complication following surgery for cancer of the rectum. It is not clear whether reinforcing sutures could prevent anastomotic leakage. Therefore, this study aims at evaluating the efficacy of reinforcing sutures on anastomotic leakage. Methods We searched PubMed, Embase, and the Cochrane Library databases from inception to January 31, 2023. We included studies comparing anastomosis with reinforcing sutures to anastomosis without reinforcing sutures after low anterior resection. Risk of bias was assessed by the Cochrane tool for RCTs and the Risk of Bias in Non‐Randomized Studies (ROBINS)‐I tool for observational studies. The overall quality of evidence for primary outcome was assessed using Grading of Recommendations Assessment, Development, and Evaluations methodology. Results Two RCTs (345 patients) and four observational studies (783 patients) were included. Anastomotic leakage occurred in 4.4% (24 of 548) of patients with reinforcing sutures and 11.9% (69 of 580) of patients without reinforcing sutures. Meta‐analysis showed a lower incidence of anastomotic leakage (RR, 0.41; 95% CI 0.25 to 0.66, low certainty) in patients with reinforcing sutures. Operative time (WMD, −3.66; 95% CI −18.58 to 11.25) and reoperation for anastomotic leakage (RR, 0.69; 95% CI 0.23 to 2.08) were similar between patients with reinforcing sutures and those without reinforcing sutures. Conclusions While observational data suggest that, there is a clear benefit in terms of reducing the risk of anastomotic leakage with the use of reinforcing sutures, RCT data are less clear. Further large, prospective studies are warranted to determine whether a true clinically important benefit exists with this technique.

Uterine corpus endometrial carcinoma (UCEC) is one of the most common type of gynecological malignancies. Multiple lines of evidence indicated that CXC chemokines exerted an anti-tumor immunological role in the tumor microenvironment which were critical regulators of cancer immunity. However, the relevance of CXC chemokines in the evaluation of prognosis and immune infiltration of UCEC remains to be explored. This study utilized various online databases, including TCGA, UALCAN, Kaplan-Meier Plotter, cBioPortal, TIMER2.0, TISIDB, and MethSurv to perform the analysis. Gene expression data from the TCGA-UCEC dataset indicated decreased expression of CXCL2/12 and increased expression of CXCL14/17. CXCL2/12 expression was negatively whereas CXCL14/17 expression was positively correlated with clinicopathological features of UCEC patients, including cancer stage, patients' age, weight and menopause status. Patients with higher CXCL12/14 expression corresponded with better clinical outcomes, which were not influenced by the genetic alterations. The differential expression of CXCL2/12/14/17 was not only significantly correlated with immune infiltration levels, but also the abundance of immune checkpoint inhibitors. Heatmaps of DNA methylation of CXCL2/12/14/17 were investigated, and 4 CpGs of CXCL2, 16 CpGs of CXCL12, 3 CpGs of CXCL14/17 were identified where altered methylation affected the prognosis of UCEC patients. These findings provided novel insights into the immunologic features of UCEC and might pave the way toward the prognostic evaluation and immunotherapy selection based on CXCL2/12/14/17 expression status.

Abstract Background Gastric cancer (GC) ranks second in mortality among all malignant diseases worldwide. However, the cause and molecular mechanism underlying gastric cancer are not clear. Here, we used integrated bioinformatics to identify possible key genes and reveal the pathogenesis and prognosis of gastric cancer. Methods The gene expression profiles of GSE118916, GSE79973, and GSE29272 were available from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between GC and normal gastric tissues were screened by R software and Venn diagram software. GO and KEGG pathway enrichment of DEGs was performed using the DAVID database. A protein-protein interaction (PPI) network was established by STRING and visualized using Cytoscape software. Then the influence of hub genes on expression and survival was assessed using TCGA database. Results A total of 83 DEGs were found in the three datasets, including 41 up-regulated genes and 42 down-regulated genes. These DEGs were mainly enriched in extracellular matrix organization and cell adhesion. The enriched pathways obtained in the KEGG pathway analysis were extracellular matrix (ECM)-receptor interaction and focal adhesion. A PPI network of DEGs was analyzed using the Molecular Complex Detection (MCODE) app of Cytoscape. Four genes were considered hub genes, including COL5A1, FBN1, SPARC, and LUM. Among them, LUM was found to have a significantly worse prognosis based on TCGA database. Conclusions We screened DEGs associated with GC by integrated bioinformatics analysis and found one potential biomarker that may be involved in the progress of GC. This hub gene may serve as a guide for further molecular biological experiments.

METTL3-mediated RNA N6-methyladenosine (m6A) is the most prevalent modification that participates in tumor initiation and progression via governing the expression of their target genes in cancers. However, its role in tumor cell metabolism remains poorly characterized. In this study, m6A microarray and quantitative proteomics were employed to explore the potential effect and mechanism of METTL3 on the metabolism in GC cells. Our results showed that METTL3 induced significant alterations in the protein and m6A modification profile in GC cells. Gene Ontology (GO) enrichment indicated that down-regulated proteins were significantly enriched in intracellular mitochondrial oxidative phosphorylation (OXPHOS). Moreover, the protein-protein Interaction (PPI) network analysis found that these differentially expressed proteins were significantly associated with OXPHOS. A prognostic model was subsequently constructed based on the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases, and the high-risk group exhibited a worse prognosis in GC patients. Meanwhile, Gene Set Enrichment Analysis (GSEA) demonstrated significant enrichment in the energy metabolism signaling pathway. Then, combined with the results of the m6A microarray analysis, the intersection molecules of DEPs and differential methylation genes (DMGs) were significantly correlated with the molecules of OXPHOS. Besides, there were significant differences in prognosis and GSEA enrichment between the two clusters of GC patients classified according to the consensus clustering algorithm. Finally, highly expressed and highly methylated molecules regulated by METTL3 were analyzed and three (AVEN, DAZAP2, DNAJB1) genes were identified to be significantly associated with poor prognosis in GC patients. These results signified that METTL3-regulated DEPs in GC cells were significantly associated with OXPHOS. After combined with m6A microarray analysis, the results suggested that these proteins might be implicated in cell energy metabolism through m6A modifications thus influencing the prognosis of GC patients. Overall, our study revealed that METTL3 is involved in cell metabolism through an m6A-dependent mechanism in GC cells, and indicated a potential biomarker for prognostic prediction in GC.

Abnormal N6-methyladenosine (m6A) modification levels caused by METTL3 have been identified to be a critical regulator in human cancers, and its roles in the immune microenvironment and the relationship between targeted therapy and immunotherapy sensitivity in gastric cancer (GC) remain poorly understood. In this study, we assessed the transcriptome-wide m6A methylation profile after METTL3 overexpression by m6A sequencing and RNA sequencing in BGC-823 cells. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to analyze the function of core targets of METTL3. Eighteen methylation core molecules were identified in GC patients by combining transcriptome and methylome sequencing. GC patients can be separated into two subtypes based on the expression of 18 methylation core molecules. Furthermore, subgroup analysis showed that patients with different subtypes had a different OS, PFS, stage, grade, and TMB. Gene set enrichment analysis (GSEA) showed that immune-related pathways were enriched among subtype A. The ESTIMATE analysis suggested that the extent of infiltration of immune cells was different in two subtypes of GC patients. Tumor Immune Dysfunction and Exclusion (TIDE) and The Cancer Immunome Atlas (TCIA) database also showed that there were significant differences in the efficacy of immunotherapy among different types of GC patients. Altogether, our results reveal that METTL3-mediated m6A methylation modification is associated with the immune microenvironment and the effects of immunotherapy in GC patients. Our findings provide novel insights for clinicians in the diagnosis and optimal treatment of GC patients.

We examined the variation in the solidification microstructure of AlSi10Mg alloy powder over a wide range of cooling rates controlled by using the fast scanning calorimetry (FSC) technique. Two exothermic peaks derived from the primary solidification of the α-Al phases and the α-Al/Si eutectic reaction were detected. These exothermic peaks became broader and shifted to lower temperatures at higher cooling rates. Focus ion beam (FIB) milling enables microstructural characterization of AlSi10Mg powder solidified at controlled cooling rates above 102 °C·s−1 in the FSC equipment. The sample solidified at 4 × 104 °C·s−1 exhibited a fine microstructure consisting of a primary α-Al phase surrounded by lamellar-shaped Si phases. The fraction of the Si phase continuously decreased with increasing cooling rate, indicating higher content of solute Si element in the α-Al phase solidified at a higher cooling rate. The secondary dendrite arm spacing (λ) of the primary α-Al phase decreased in the sample solidified at a higher cooling rate (dT/dt). The relation follows a general equation of λ = A (dT/dt)-n (A: 38.4, n: 0.33) in wide range of cooling rate (10-1 ∼ 104 °C·s−1). The results were utilized to discuss the cooling rate of Al alloys during the laser powder bed fusion (L-PBF) process.

Objective: m7G is a post-transcriptional modification modality, however, limited research has been conducted on its role in colon cancer. DNA damage repair (DDR) is an important factor that contributes to colon cancer development, growth and chemoresistance. This study aimed to explore whether m7G-related DNA damage repair genes may be used as biomarkers to predict the prognosis of colon cancer patients.Methods: We use non-negative matrix factorization (NMF) to type CRC patients into. Risk models were constructed using different expression genes in two clusters. We assessed the reliability of risk models with DCA curves, and a Nomogram. Meanwhile, The receiver operating characteristic and C-index curves were used to compare the predictive significance of the constructed risk models with other studies. In additional, we examined the significance of risk models on patients’ immunity microenvironment and response to immune therapy. Finally, we used a series of cellular experiments to validate the effect of model genes on the malignant progression of CRC cells.Results: Twenty-eight m7G genes were obtained from the GSEA database. Multivariate Cox and LASSO Cox regression analysis was performed and eleven m7G-related DDR genes were identified for constructing the risk model. Survival and stage of CRC patients were worser in the high-risk group than in the low-risk group for both the training and test sets. Additionally, the different immune microenvironment status of patients in the high- and low-risk groups, suggesting that patients in the low-risk group may be more sensitive to immunotherapy, particularly immune checkpoint inhibitors. Finally, we found that depletion of ATP2A1, one of the risk genes in our model, influence the biologic behaviour of CRC cells significantly.Conclusion: The m7G-related DDR genes can be used as important markers for predicting patient prognosis and immunotherapy response. Our data suggest that ATP2A1 may promote the proliferation of colon cancer cells. These findings may provide new therapeutic targets for the treatment of colon cancer.

In this study, we analyzed GPC family genes in colorectal cancer (CRC) and the possible mechanism of action of GPC1 in CRC. CRC patient data were extracted from The Cancer Genome Atlas, and the prognostic significance of GPC1 expression and its association with clinicopathological features were identified by Kolmogorov–Smirnov test. CRC patients with high GPC1 expression had poor overall survival compared with patients with low GPC1 expression. In vitro experiments demonstrated that knockdown of GPC1 significantly inhibited the proliferation and migration and promoted cell apoptosis in CRC cell lines. Gene Ontology analysis of differential genes indicated that GPC1 may influence the TGF-β1 signaling pathway. Additional experiments revealed that silencing GPC1 suppressed the levels of TGF-β1 and p-SMAD2 but increased the expression of SMAD2. Taken together, these findings suggest that GPC1 may function as a tumor promoter in CRC cells through promoting TGF-β signaling pathway. Our results also indicate that GPC1 may serve as a critical effector in CRC progression and a new potential target for CRC therapy.

In order to manage both the strength and ductility of Al–Si alloys additively manufactured by laser powder bed fusion (L-PBF), an attempt was made to introduce nanoscale precipitates within the α-Al (fcc) supersaturated solid solution using the L-PBF manufactured Al–12%Si alloy by artificial aging treatments. The aging treatment at 120°C improved both the tensile strength and ductility (total elongation) of the L-PBF manufactured specimen. The simultaneous strength–ductility enhancement is due to the homogeneously distributed nanoscale Si precipitates that enhanced the strain hardening. These results provide new insights for overcoming the strength-ductility trade-off in the L-PBF manufactured Al alloys.