Comprehensive prognostic assessment in kidney cancer: A multidimensional approach analyzing Fufang Sanling granules, genetic variants, and immune infiltration.

This study delves into the potential therapeutic benefits of Fufang Sanling Granules for kidney cancer, focusing on their active components and the underlying mechanisms of their interaction with cancer-related targets. By constructing a drug-active component-target network based on eight herbs, key active compounds such as kaempferol, quercetin, and linolenic acid were identified, suggesting their pivotal roles in modulating immune responses and cellular signaling pathways relevant to cancer progression. The research further identified 51 central drug-disease genes through comprehensive bioinformatics analyses, implicating their involvement in crucial biological processes and pathways. A novel risk score model, encompassing six genes with significant prognostic value for renal cancer, was established and validated, showcasing its effectiveness in predicting patient outcomes through mutation analysis and survival studies. The model's predictive power was further confirmed by its ability to stratify patients into distinct risk groups with significant survival differences, highlighting its potential as a prognostic tool. Additionally, the study explored the relationship between gene expression within the identified black module and the risk score, uncovering significant associations with the extracellular matrix and immune infiltration patterns. This reveals the complex interplay between the tumor microenvironment and cancer progression. The integration of the risk score with clinical parameters through a nomogram significantly improved the model's predictive accuracy, offering a more comprehensive tool for predicting kidney cancer prognosis. In summary, by combining detailed molecular analyses with clinical insights, this study presents a robust framework for understanding the therapeutic potential of Fufang Sanling Granules in kidney cancer. It not only sheds light on the active components and their interactions with cancer-related genes but also introduces a reliable risk score model, paving the way for personalized treatment strategies and improved patient management in the future.

Neutrophil extracellular traps promote gastric cancer cell metastasis via the NAT10-mediated N4-acetylcytidine modification of SMYD2.

It has been reported that the formation of neutrophil extracellular traps (NETs) is associated with cancer metastasis. The current study aimed to explore the effects of NETs on gastric cancer (GC) cell metastasis and uncover their underlying mechanism. NETs were measured in the plasma of patients with GC. Then, GC cells were treated with NETs to assess cell viability, migration, and invasion using cell counting kit 8 and Transwell assay, The liver metastasis and xenograft tumor mouse models were established to assess tumor growth and metastasis. The N4-acetylcytidine (ac4C) modification of SET and MYND domain containing 2 (SMYD2) mediated by NAT10 was evaluated using acetylated RNA immunoprecipitation. The results showed that the level of NETs was increased in the plasma of patients with GC, particularly in those with metastatic GC. In addition, GC cell co-treatment with NETs promoted cell viability, migration and invasion, while NAT10 or SMYD2 knockdown abrogated this effect. NAT10 also promoted the ac4C modification of SMYD2, thus increasing SMYD2 stability. Furthermore, NETs promoted the metastasis of GC cells in the liver in vivo. Overall, the results of the present study demonstrated that NETs promoted GC cell metastasis via the NAT10-mediated ac4C modification of SMYD2. These findings suggested that inhibiting the formation of NETs could be an effective approach for attenuating GC progression.

A RBM47 and IGF2BP1 mediated circular FNDC3B-FNDC3B mRNA imbalance is involved in the malignant processes of osteosarcoma.

BACKGROUND: Circular RNAs (circRNAs) are a class of noncoding RNAs that are involved in the progression of many human cancers. The precise gene locus and the roles of circular RNA from Fibronectin type III domain containing 3B (FNDC3B) in OS and its mechanisms of action have not been fully explored. MATERIALS AND METHODS: qRT-qPCR assay was used to determine gene expressions. CCK8 Assay, EdU assay, wound-healing assay, transwell invasion assay and in vivo xenograft assay were used to perform functional investigations. RNA-FISH, immunofluorescence, RIP assay, RNA stability analysis were applied in mechanistic studies. RESULTS: We found that circFNDC3B downregulated and FNDC3B mRNA upregulated in OS, and might be potential biomarkers for indicating disease progression and prognosis of OS patients. CircFNDC3B acted as a tumor suppressor gene to restrain OS progression and FNDC3B functioned as an oncogene to promote OS progression in vitro and in vivo. RNA binding protein RNA binding motif protein 47 (RBM47) could bind to the flanking introns of circFNDC3B to facilitate the generation of circFNDC3B, resulting in the reduction of FNDC3B mRNA and the circFNDC3B-FNDC3B mRNA imbalance. CircFNDC3B also inhibited FNDC3B mRNA expression by reducing its stability via competitively binding to Insulin-like growth-factor-2 mRNA binding protein (IGF2BP1). CONCLUSION: This study demonstrated that RBM47 and IGF2BP1 mediated circular FNDC3B/FNDC3B mRNA imbalance was involved in the malignant processes of OS.

Novel nomogram to predict the overall survival of postoperative patients with gastric signet.

BACKGROUND: The TNM staging system cannot accurately predict the prognosis of postoperative gastric signet ring cell carcinoma (GSRC) given its unique biological behavior, epidemiological features, and various prognostic factors. Therefore, a reliable postoperative prognostic evaluation system for GSRC is required. This study aimed to establish a nomogram to predict the overall survival (OS) rate of postoperative patients with GSRC and validate it in the real world. METHODS: Clinical data of postoperative patients with GSRC from 2002 to 2014 were collected from the Surveillance, Epidemiology, and End Results database and randomly assigned to training and internal validation sets at a 7:3 ratio. The external validation set used data from 124 postoperative patients with GSRC who were admitted to the Affiliated Tumor Hospital of Harbin Medical University between 2002 and 2014. The independent risk factors affecting OS were screened using univariate and multivariate analyses to construct a nomogram. The performance of the model was evaluated using the C-index, receiver operating characteristic curve (ROC), calibration curve, decision analysis (DCA) curve, and adjuvant chemotherapy decision analysis. RESULTS: Univariate/multivariate analysis indicated that age, stage, T, M, regional nodes optimized (RNE), and lymph node metastasis rate (LNMR) were independent risk factors affecting prognosis. The C-indices of the training, internal validation, and external validation sets are 0.741, 0.741, and 0.786, respectively. The ROC curves for the first, third, and fifth years in three sets had higher areas under the curves, (training set, 0.782, 0.864, 0.883; internal validation set, 0.781, 0.863, 0.877; external validation set, 0.819, 0.863, 0.835). The calibration curve showed high consistency between the nomogram-predicted 1-, 3-, and 5-year OS and the actual OS in the three queues. The DCA curve indicated that applying the nomogram enhanced the net clinical benefits. The nomogram effectively distinguished patients in each subgroup into high- and low-risk groups. Adjuvant chemotherapy can significantly improve OS in high-risk group (P = 0.034), while the presence or absence of adjuvant chemotherapy in low-risk group has no significant impact on OS (P = 0.192). CONCLUSIONS: The nomogram can effectively predict the OS of patients with GSRC and may help doctors make personalized prognostic judgments and clinical treatment decisions.

SMYD Family Members Serve as Potential Prognostic Markers and Correlate with Immune Infiltrates in Gastric Cancer.

Background: The SMYD family comprises a group of genes encoding lysine methyltransferases, which are closely related to tumorigenesis. However, a systematic understanding of their role in gastric cancer (GC) is lacking. Methods: Using databases and tools such as the Cancer Genome Atlas, Human Protein Atlas, Kaplan-Meier Plotter, Gene Expression Profiling Interactive Analysis, and Metascape, we comprehensively analyzed differences in SMYD expression and its prognostic value as well as the association of SMYDs with immune cell infiltration, tumor mutational burden (TMB), and microsatellite instability (MSI). We conducted functional enrichment analysis and explored a competing endogenous RNA mechanism regulating SMYD mRNA and protein levels in patients with GC. Results: In GC, the expression of SMYD2/3/4/5 mRNA was significantly upregulated, as opposed to that of SMYD1 mRNA, which was significantly downregulated. The protein levels of SMYDs were consistent with mRNA levels. SMYD1/2/4/5 was negatively correlated with overall survival; SMYD1/2/3/5 was negatively correlated with progression-free survival. Our SMYD-based signature and nomogram model may be useful for inferring the prognosis of GC. All SMYDs were closely associated with the infiltration of six immune cell types: uncharacterized, CD8+ T, CD4+ T, macrophage, endothelial, and B cells. TMB was significantly negatively correlated with SMYD1 expression, while a significant positive correlation was observed with SMYD2/5. Furthermore, MSI was significantly positively correlated with SMYD2/5 expression. Long non-coding RNAs, such as chr22-38_28785274-29006793.1, XLOC_002309, and CTD-2008N3.1, were suggested to regulate SMYD expression by sponging multiple microRNAs. Conclusion: SMYDs are differentially expressed in GC and are thus potential prognostic markers. SMYD expression is closely related to immune infiltration, TMB, and MSI, all of which are closely related to the response to targeted immune therapy.

Induction of p27 contributes to inhibitory effect of isorhapontigenin (ISO) on malignant transformation of human urothelial cells.

Bladder cancer (BC) is the most expensive cancer to manage on a per-patient basis, costing about $4 billion in total healthcare expenditure per annum in America alone. Therefore, identifying a natural compound for prevention of BC is of tremendous importance for managing this disease. Previous studies have identified isorhapontigenin (ISO) as having an 85% preventive effect against invasive BC formation induced by N-butyl-N-(4-hydroxybutyl) nitrosamine (BBN). The results showed here that ISO treatment inhibited EGF-induced cell transformation of human urothelial cells through induction of tumor suppressor p27 transcription secondary to activation of an E2F1-dependentpathway.ISOtreatmentrenderedcellsresistanttoEGF-induced anchorage-independent growth concurrent with p27 protein induction in both UROtsa and SV-HUC-1 cells. ISO inhibition of EGF-induced cell transformation could be completely reversed by knockdown of p27, indicating that this protein was essential for the noted ISO inhibitory action. Mechanistic studies revealed that ISO treatment resulted in increased expression of E2F1, which in turn bound to its binding site in p27 promoter and initiated p27 transcription. The E2F1 induction was due to the elevation of its translation caused by ISO-induced miR-205 downregulation. Consistently, miR-205 was found to be overexpressed in human BCs, and ectopic expression of miR-205 mitigated ISO inhibitory effects against EGF-induced outcomes. Collectively, the results here demonstrate that ISO exhibits its preventive effect on EGF-induced human urothelial cell transformation by induction of p27 through a miR-205/E2F1 axis. This is distinct from what has been described for the therapeutic effects of ISO on human BC cells.

Machine Learning-Based Model for the Prognosis of Postoperative Gastric Cancer.

BACKGROUND: The use of machine learning (ML) in predicting disease prognosis has increased, and scientists have adopted different methods for cancer classification to optimize the early screening of cancer to determine its prognosis in advance. In this study, we aimed at improving the prediction accuracy of gastric cancer in postoperation patients by constructing a highly effective prognostic model. METHODS: The study used postoperative gastric cancer patient data from the SEER database. The LASSO regression method was used to construct a clinical prognostic model, and four machine learning methods (Boruta algorithm, neural network, support vector machine, and random forest) were used to screen and recombine the features to construct an ML prognostic model. Clinical information on 955 postoperative gastric cancer patients collected from the Affiliated Tumor Hospital of Harbin Medical University was used for external verification. RESULTS: Experimental results showed that the AUC values of 1, 3 and 5 years in the training set, validation set and external validation set of clinical prognosis model and ML prognosis model directly established by LASSO regression are all around 0.8. CONCLUSION: Both models can accurately evaluate the prognosis of postoperative patients with gastric cancer, which may be helpful for accurate and personalized treatment of postoperative patients with gastric cancer.

Recognition of DNA Methylation Molecular Features for Diagnosis and Prognosis in Gastric Cancer.

Background: The management of gastric cancer (GC) still lacks tumor markers with high specificity and sensitivity. The goal of current research is to find effective diagnostic and prognostic markers and to clarify their related mechanisms. Methods: In this study, we integrated GC DNA methylation data from publicly available datasets obtained from TCGA and GEO databases, and applied random forest and LASSO analysis methods to screen reliable differential methylation sites (DMSs) for GC diagnosis. We constructed a diagnostic model of GC by logistic analysis and conducted verification and clinical correlation analysis. We screened credible prognostic DMSs through univariate Cox and LASSO analyses and verified a prognostic model of GC by multivariate Cox analysis. Independent prognostic and biological function analyses were performed for the prognostic risk score. We performed TP53 correlation analysis, mutation and prognosis analysis on eleven-DNA methylation driver gene (DMG), and constructed a multifactor regulatory network of key genes. Results: The five-DMS diagnostic model distinguished GC from normal samples, and diagnostic risk value was significantly correlated with grade and tumor location. The prediction accuracy of the eleven-DMS prognostic model was verified in both the training and validation datasets, indicating its certain potential for GC survival prediction. The survival rate of the high-risk group was significantly lower than that of the low-risk group. The prognostic risk score was an independent risk factor for the prognosis of GC, which was significantly correlated with N stage and tumor location, positively correlated with the VIM gene, and negatively correlated with the CDH1 gene. The expression of CHRNB2 decreased significantly in the TP53 mutation group of gastric cancer patients, and there were significant differences in CCDC69, RASSF2, CHRNB2, ARMC9, and RPN1 between the TP53 mutation group and the TP53 non-mutation group of gastric cancer patients. In addition, CEP290, UBXN8, KDM4A, RPN1 had high frequency mutations and the function of eleven-DMG mutation related genes in GC patients is widely enriched in multiple pathways. Conclusion: Combined, the five-DMS diagnostic and eleven-DMS prognostic GC models are important tools for accurate and individualized treatment. The study provides direction for exploring potential markers of GC.

Comprehensive Analysis of the Value of SMYD Family Members in the Prognosis and Immune Infiltration of Malignant Digestive System Tumors.

BACKGROUND: The SET and MYND domain-containing (SMYD) gene family comprises a set of genes encoding lysine methyltransferases. This study aimed to clarify the relationship between the expression levels of SMYD family members and the prognosis and immune infiltration of malignant tumors of the digestive system. METHODS: The Oncomine, Ualcan, Kaplan-Meier Plotter, cBioPortal, Metascape, and TIMER databases and tools were used to analyze the correlation of SMYD family mRNA expression, clinical stage, TP53 mutation status, prognostic value, gene mutation, and immune infiltration in patients with esophageal carcinoma (ESCA), liver hepatocellular carcinoma (LIHC), and stomach adenocarcinoma (STAD). RESULTS: In ESCA, the mRNA expression of SMYD2/3/4/5 was significantly correlated with the incidence rate, that of SMYD2/3 with the clinical stage, that of SMYD2/3/4/5 with TP53 mutation status, that of SMYD2/4/5 with overall survival (OS), and that of SMYD1/2/3/4 with relapse-free survival (RFS). In LIHC, the mRNA expression of SMYD1/2/3/4/5 was significantly correlated with the incidence rate, that of SMYD2/4/5 with the clinical stage, that of SMYD3/5 with TP53 mutation status, that of SMYD2/3/4/5 with OS, and that of SMYD3/5 with RFS. In STAD, the mRNA expression of SMYD2/3/4/5 was significantly correlated with the incidence rate, that of SMYD1/4 with the clinical stage, that of SMYD1/2/3/5 with TP53 mutation status, that of SMYD1/3/4 with OS, and that of SMYD1/3 with RFS. Furthermore, the function of SMYD family mutation-related genes in ESCA, LIHC, and STAD patients was mainly related to pathways, such as mitochondrial gene expression, mitochondrial matrix, and mitochondrial translation. The expression of SMYD family genes was significantly correlated with the infiltration of six immune cell types and eight types of immune check sites. CONCLUSION: SMYD family genes are differentially expressed and frequently mutated in malignant tumors of the digestive system (ESCA, LIHC, and gastric cancer). They are potential markers for prognostic prediction and have important significance in immunity and targeted therapy.

A tetrahedral DNA nanostructure-decorated electrochemical platform for simple and ultrasensitive EGFR genotyping of plasma ctDNA.

Genotyping of the epidermal growth factor receptor (EGFR) mutation status is of great importance in the screening of appropriate patients with advanced non-small cell lung carcinoma (NSCLC) to receive superior tyrosine kinase inhibitor (TKIs) therapy. Yet conventional assays are generally costly with a relatively long turnaround time for obtaining results, which can lead to a bottleneck for immediately starting TKI therapy in late-staged patients. In this study, we propose an on-site electrochemical platform for sensitive simultaneous genotyping of the two major EGFR mutations (19del and L858R) through plasma ctDNA based on tetrahedral DNA nanostructure decorated screen-printed electrodes (SPE). Linear-after-the-exponential (LATE)-PCR combined with the amplification refractory mutation system (ARMS) was adopted to produce abundant biotin-labeled single-stranded DNA with high amplification efficiency and specificity. Disposable SPE decorated with self-assembled tetrahedral nanostructured DNA probes that showed ordered orientation and good target accessibility enabled the highly efficient hybridization of the specific amplicons through a sandwich-type and quantitatively translated the interfacial hybridization event into electrochemical signals via enzymatic amplification. Taking advantage of the ARMS-based LATE-PCR and the tetrahedral nanostructure-decorated SPE platform, we achieved the accurate detection of around 30 pg DNA of 19del or L858R, or as low as 0.1% of them in the presence of wild-type DNA. Moreover, the EGFR mutation profiles of 13 NSCLC patients we enlisted were accurately genotyped by our electrochemical platform, the results of which were in good agreement with those of commercial genetic detection methods.

Silencing of SENP2 in Multiple Myeloma Induces Bortezomib Resistance by Activating NF-κB Through the Modulation of IκBα Sumoylation.

The proteasome inhibitor bortezomib is the most successfully applied chemotherapeutic drug for treating multiple myeloma. However, its clinical efficacy reduced due to resistance development. The underlying molecular mechanisms of bortezomib resistance are poorly understood. In this study, by combining in silico analysis and sgRNA library based drug resistance screening assay, we identified SENP2 (Sentrin/SUMO-specific proteases-2) as a bortezomib sensitive gene and found its expression highly downregulated in bortezomib resistant multiple myeloma patient's samples. Furthermore, down regulation of SENP2 in multiple myeloma cell line RPMI8226 alleviated bortezomib induced cell proliferation inhibition and apoptosis, whereas, overexpression of SENP2 sensitized these cells to bortezomib treatment. We further demonstrate that knockdown of SENP2 in RPMI8226 cells increased SUMO2 conjugated IκBα that resulted in the activation of NF-κB. Taken together, we report that silencing of SENP2 and consequent activation of NF-κB through the modulation of IκBα sumoylation as a novel mechanism inducing bortezomib resistance in multiple myeloma.

Integrated network analysis identifies hsa-miR-4756-3p as a regulator of FOXM1 in Triple Negative Breast Cancer.

Both aberrantly expressed mRNAs and micro(mi)RNAs play important roles in cancer cell function, which makes integration analysis difficult. In this study, we first applied master regulator analysisalgorithm and confirmed hsa-miR-4756-3p as a candidate miRNA in triple negative breast cancer (TNBC) patients; hsa-miR-4756-3p could regulate TNBC cell line apoptosis, proliferation, migration, and cell cycle as well as suppress TGF-ß1 signalling andtumour growth. In TNBC, forkhead box protein M1 (FOXM1)was found to be an hsa-miR-4756-3p target gene, and FOXM1 knockout completely inhibited hsa-miR-4756-3p-induced cell migration and metastasis, TGF-ß1 signalling, and epithelial mesenchymal signal activation, which indicated that hsa-miR-4756-3p functions via the FOXM1-TGFß1-EMT axis.

Single copy-sensitive electrochemical assay for circulating methylated DNA in clinical samples with ultrahigh specificity based on a sequential discrimination-amplification strategy.

Tumor-related circulating methylated DNA represents only a small fraction of the total DNA in clinical samples (e.g. plasma), challenging the accurate analysis of specific DNA methylation patterns. Yet conventional assays based on the real-time quantitative methylation-specific PCR (qMSP) are generally limited in detection sensitivity and specificity due to its non-specific amplification interference including primer dimers and off-target amplification. Here we propose a single copy-sensitive electrochemical assay for circulating methylated DNA with ultrahigh specificity on the basis of a sequential discrimination-amplification strategy. Methylated DNA rather than unmethylated DNA in a bisulfite-modified sample is identified and amplified by the asymmetric MSP to generate abundant biotin-labeled single-stranded amplicons with reduced primer-dimer artifacts. Self-assembled tetrahedral DNA probes, which are readily decorated on an electrode surface as nanostructured probes with ordered orientation and well controlled spacing, enable the highly efficient hybridization of the specific single-stranded amplicons due to greatly increased target accessibility and significantly decreased noise. The interfacial hybridization event is quantitatively translated into electrochemical signals utilizing an enzymatic amplification. The proposed assay integrates dual sequence discrimination processes and cascade signal amplification processes, achieving the identification of as few as one methylated DNA molecule in the presence of a 1000-fold excess of unmethylated alleles. Furthermore, the excellent assay performance enables tumor related methylation detection in lung cancer patients with 200 microlitre plasma samples. The results are in good consistency with those of clinical diagnosis, whereas the conventional qMSP failed to detect the corresponding methylation pattern of these clinically confirmed positive patients in such trace amounts of samples.

Accurate Electrochemistry Analysis of Circulating Methylated DNA from Clinical Plasma Based on Paired-End Tagging and Amplifications.

Circulating methylated DNA has been a new kind of cancer biomarker, yet its small fraction of trace total DNA from clinical samples impairs the accurate analysis. Though fluorescence methods based on quantitative methylation specific PCR (qMSP) have been adopted routinely, yet alternative electrochemistry assay of such DNA from clinical samples remains a great challenge. Herein, we report accurate electrochemistry analysis of circulating methylated DNA from clinical plasma samples based on a paired-end tagging and amplifications strategy. Two DNA primers each labeled with digoxigenin (Dig) and biotin are designed for the recognition and amplification of methylated DNA. Paired-end tagging amplicons and avidin-HRP molecules are successively captured on the electrode modified with Anti-Dig. Then HRP executes catalytic reaction to generate amplified signal. The design of paired-end tagging can readily integrate downstream electrochemical amplified reaction, and two heterogeneous amplifications enable high assay sensitivity. As little as 40 pg of methylated genomic DNA (∼10 genomic equivalents) is well identified, and our strategy can even distinguish as low as 1% methylation level. Tumor-specific methylated DNA is clearly detected in the plasma of 10 of 11 NSCLC patients. The high clinical sensitivity of 91% (10/11) indicates the good consistency with clinical diagnosis. Excellent spatial control of electrochemistry allows simpler detection of more methylation patterns compared to fluorescence methods. The developed electrochemical assay is a promising liquid biopsy tool for the analysis of tumor-specific circulating DNA.