The role of histological subtype and chemotherapy on prognosis of ureteral cancer.

OBJECTIVE: To date, there have been few studies examining the prognostic implications of histological subtypes in ureteral cancer. And chemotherapy plays a crucial role in the treatment of ureteral cancer, while many factors influence the efficacy of chemotherapy. This study aimed to utilize the Surveillance, Epidemiology and End Results database to assess the impact of histological type on ureteral cancer prognostic outcomes and discovered how histological type and T-stage influence the efficacy of chemotherapy. METHODS: Based on Surveillance, Epidemiology, and End Results Program, we reviewed 8915 records of patients with primary ureteral cancer from 18 centers between 2000 and 2018. We focused on the overall survival and cancer-specific survival of the records and used Kaplan‒Meier method to calculate survival curves. RESULTS: In the comparison of prognostic outcomes, atypical subtypes exhibited a less favorable prognosis compared to typical ureteral carcinoma. Notably, patients diagnosed with papillary urothelial carcinoma demonstrated the most favorable overall survival (p = 0.005). Statistically significant benefits were observed in the prognosis of patients with non-papillary urothelial carcinoma who received chemotherapy (HR = 0.860, 95% CI 0.764-0.966, p = 0.011), while chemotherapy did not yield a statistically significant effect on the prognosis of patients with papillary urothelial carcinoma (HR = 1.055, 95% CI 0.906-1.228, p = 0.493). Chemotherapy had an adverse impact on the prognosis of patients with T1 ureteral cancer (HR = 1.235, 95% CI 1.016-1.502, p = 0.034), whereas it exhibited a positive prognostic effect for T3/T4 cases (HR = 0.739, 95% CI 0.654-0.835, p < 0.001). CONCLUSIONS: Histological type affects the prognosis of ureteral cancer. And evaluation of cancer histological type and T stage in ureteral cancer patients prior to chemotherapy is mandatory.

Molecular modeling of CO2 affecting competitive adsorption within anthracite coal.

This study aimed to investigate the adsorption properties of CO2, CH4, and N2 on anthracite. A molecular structural model of anthracite (C208H162O12N4) was established. Simulations were performed for the adsorption properties of single-component and multi-component gases at various temperatures, pressures, and gas ratios. The grand canonical ensemble Monte Carlo approach based on molecular mechanics and dynamics theories was used to perform the simulations. The results showed that the isotherms for the adsorption of single-component CO2, CH4, and N2 followed the Langmuir formula, and the CO2 adsorption isotherm growth gradient was negatively correlated with pressure but positively correlated with temperature. When the CO2 injection in the gas mixture was increased from 1 to 3% for the multi-component gas adsorption, the proportion of CO2 adsorption rose from 1/3 to 2/3, indicating that CO2 has a competing-adsorption advantage. The CO2 adsorption decreased faster with increasing temperature, indicating that the sensitivity of CO2 to temperature is stronger than that of CH4 and N2. The adsorbent potential energies of CO2, CH4, and N2 diminished with rising temperature in the following order: CO2 < CH4 < N2.

Systematic identification of key basement membrane related genes as potential new biomarkers in Alzheimer's disease.

OBJECTIVE: The study aimed to identify biomarkers associated with basement membranes (BMs)-related genes (BMGs) in Alzheimer's disease (AD) and investigate their potential role in the progression of AD pathology. METHODS: Gene expression profiles were retrieved from Gene Expression Omnibus database. 222 human BMGs were collected from the relevant literature. Subsequently, the differentially expressed BMGs (DE-BMGs) were filtered, and the key DE-BMGs were identified using weighted gene correlation network analysis (WGCNA) and two machine learning algorithms. The expression levels, diagnostic values, clinical significances, enrichment analyses and regulatory networks of these candidate biomarkers were further examined. RESULTS: A total of 44 DE-BMGs were acquired by comparing AD temporal cortex with nondemented controls. Using WGCNA and machine learning, versiscan (VCAN), tissue inhibitor of metalloproteinase 1 (TIMP1), structural maintenance of chromosome 3 (SMC3), and laminin ß2 (LAMB2) were ultimately identified as candidate biomarkers, and they were verified in a murine model. These biomarkers had high diagnostic value (area under the curve (AUC)＞0.8). The diagnostic value of the four gene combination was then evaluated in multiple databases, yielding AUCs ranging from 0.688 to 1. Furthermore, a meaningful correlation between these biomarkers and AD pathology progression was observed. Finally, comprehensive analyses involving Hallmark pathway enrichment, immune cell infiltration analysis, transcriptional regulatory, and competitive endogenous RNA networks indicated that key DE-BMGs closely correlated with oxidative stress and immune dysfunction. CONCLUSION: Our study comprehensively identified four candidate BMGs and their combination model that play a crucial part in the diagnosis and pathogenesis of AD.

Novel insights into molecular signatures and pathogenic cell populations shared by systemic lupus erythematosus and vascular dementia.

Although vascular dementia (VD) and systemic lupus erythematosus (SLE) may share immune-mediated pathophysiologic processes, the underlying mechanisms are unclear. This study investigated shared gene signatures in SLE versus VD, as well as their potential molecular mechanisms. Bulk RNA sequencing (RNAseq) and single-cell or single-nucleus RNAseq (sc/snRNAseq) datasets from SLE blood samples and VD brain samples were obtained from Gene Expression Omnibus. The identification of genes associated with both SLE and VD was performed using the weighted gene co-expression network analysis (WGCNA) and machine learning algorithms. For the sc/snRNAseq data, an unbiased clustering pipeline based on Seurat and CellChat was used to determine the cellular landscape profile and examine intracellular communication, respectively. The results were subsequently validated using a mice model of SLE with cognitive dysfunction (female MRL/lpr mice). WGCNA and machine learning identified C1QA, LY96, CD163, and MS4A4A as key genes for SLE and VD. sc/snRNAseq analyses revealed that CD163 and MS4A4A were upregulated in mononuclear phagocytes (MPs) from SLE and VD samples and were associated with monocyte-macrophage differentiation. Intriguingly, LGALS9-associated molecular pathway, as the only signaling pathway common between SLE and VD via CellChat analysis, exhibited significant upregulation in cortical microglia of MRL/lpr mice. Our analyses identified C1QA, LY96, CD163, and MS4A4A as potential biomarkers for SLE and VD. Moreover, the upregulation of CD163/MS4A4A and activation of LGALS9 signaling in MPs may contribute to the pathogenesis of VD with SLE. These findings offer novel insight into the mechanisms underlying VD in SLE patients.

Cooperative regulation of coupled oncoprotein synthesis and stability in triple-negative breast cancer by EGFR and CDK12/13.

Evidence has long suggested that epidermal growth factor receptor (EGFR) may play a prominent role in triple-negative breast cancer (TNBC) pathogenesis, but clinical trials of EGFR inhibitors have yielded disappointing results. Using a candidate drug screen, we identified that inhibition of cyclin-dependent kinases 12 and 13 (CDK12/13) dramatically sensitizes diverse models of TNBC to EGFR blockade. This combination therapy drives cell death through the 4E-BP1-dependent suppression of the translation and translation-linked turnover of driver oncoproteins, including MYC. A genome-wide CRISPR/Cas9 screen identified the CCR4-NOT complex as a major determinant of sensitivity to the combination therapy whose loss renders 4E-BP1 unresponsive to drug-induced dephosphorylation, thereby rescuing MYC translational suppression and promoting MYC stability. The central roles of CCR4-NOT and 4E-BP1 in response to the combination therapy were further underscored by the observation of CNOT1 loss and rescue of 4E-BP1 phosphorylation in TNBC cells that naturally evolved therapy resistance. Thus, pharmacological inhibition of CDK12/13 reveals a long-proposed EGFR dependence in TNBC that functions through the cooperative regulation of translation-coupled oncoprotein stability.

A robust gene prognostic index composed of GZMB, IRF1, and TP63 can stratify the risk of two metastatic urothelial carcinoma cohorts based on immune checkpoint blockade therapy.

BACKGROUND: Immune checkpoint blockade (ICB) therapy has become a first-line treatment option for metastatic urothelial carcinoma (mUC) patients who do not meet the criteria of cisplatin. Still, only a few people can benefit from it, so useful predictive markers are needed. METHODS: Download the ICB-based mUC and chemotherapy-based bladder cancer cohorts, and extract the expression data of pyroptosis-related genes (PRG). The LASSO algorithm was used to construct the PRG prognostic index (PRGPI) in the mUC cohort, and we verified the prognostic ability of PRGPI in two mUC and two bladder cancer cohorts. RESULTS: Most of the PRG in the mUC cohort were immune-activated genes, and a few were immunosuppressive genes. The PRGPI composed of GZMB, IRF1, and TP63 can stratify the risk of mUC. In IMvigor210 and GSE176307 cohorts, the P-values of Kaplan Meier analysis was < 0.01 and 0.002, respectively. PRGPI could also predict ICB response, and the chi-square test of the two cohorts had P-values of 0.002 and 0.046, respectively. In addition, PRGPI can also predict the prognosis of two bladder cancer cohorts without ICB therapy. The PRGPI and the expression of PDCD1/CD274 had a high degree of synergistic correlation. The Low PRGPI group showed prominent characteristics of immune infiltration and was enriched in the immune signal activation pathway. CONCLUSION: The PRGPI we constructed can effectively predict the treatment response and overall survival rate of mUC patients treated with ICB. The PRGPI can help mUC patients achieve individualized and accurate treatment in the future.

Dynamic changes in the glycocalyx and clinical outcomes in patients undergoing endovascular treatments for large vessel occlusion.

Purpose: We aimed to verify the prognostic value of the glycocalyx as a marker of blood-brain barrier damage in patients with acute ischemic stroke undergoing endovascular therapy. Methods: We recruited patients with large vessel occlusion who were undergoing recanalization and tested their glycocalyx at multiple time points. On the basis of the 90-day follow-up data, the patients were divided into a survivor group and a nonsurvivor group. In addition, neurological function was tracked, and patients were divided into a neurological deterioration group and a group without neurological deterioration. Associations between outcomes and dynamic changes in the glycocalyx were determined using a linear mixed model, and significant factors were used as covariates. Results: Nonsurvivors and patients with neurological deterioration had significantly higher syndecan-1 concentrations than survivors and patients without neurological deterioration, and syndecan-1 tended to decline after endovascular therapy (p < 0.05). The increased level of syndecan-1 at 36 h after endovascular treatment was positively correlated with the National Institute of Health Stroke Scale score for neurological deterioration (r = 0.702, p = 0.005). However, there was no significant difference in the level of hyaluronic acid or heparan sulfate in the plasma of patients with different clinical outcomes. Conclusion: Pre-reperfusion syndecan-1 levels in patients with large vessel occlusion stroke are associated with 90-day mortality and the re-degradation of syndecan-1 is positively associated with neurological deterioration.

An old thrombus may potentially identify patients at higher risk of poor outcome in anterior circulation stroke undergoing thrombectomy.

PURPOSE: To investigate thrombus age and its association with clinical and procedural parameters in patients with acute ischemic stroke (AIS) due to anterior circulation occlusions. METHODS: The thrombi of 107 consecutive AIS patients with occlusions in anterior circulation large-arteries were collected during mechanical recanalization. By hematoxylin-eosin staining analysis, thrombi were classified as fresh (< 3 days) or old (≥ 3 days) according to the hemosiderin positivity. Old thrombi were further classified as thrombi with focal hemosiderin or diffuse hemosiderin according to their predominant distribution. Neuro-interventional data and clinical outcomes were compared based on thrombus age. RESULTS: We identified fresh thrombi in 29 patients and old thrombi in 78 patients. Compared with patients with fresh thrombi, patients with old thrombi were associated with (i) a longer mechanical recanalization time (p = 0.027), (ii) a higher percentage of fibrin/platelets and leukocytes (all p = 0.02) and a lower percentage of erythrocytes (p = 0.001), and (iii) less favorable clinical outcomes at discharge (p = 0.019) and 90 days later (OR = 2.76, 95% CI = 1.09-6.99, p = 0.032). Furthermore, 18 (16.8%) of all patients had focal hemosiderin in old thrombi, which was independently linked to a poor clinical outcome 90 days later (adjusted OR = 5.37, 95% CI = 1.14-25.28, p = 0.034). CONCLUSION: The presence of old thrombi, particularly those with focal hemosiderin, may aid in identifying patients with acute ischemic anterior circulation stroke who are at a higher risk of poor clinical outcome at 3-month follow-up.

Application of synthetic biology in bladder cancer.

ABSTRACT: Bladder cancer (BC) is the most common malignant tumor of the genitourinary system. The age of individuals diagnosed with BC tends to decrease in recent years. A variety of standard therapeutic options are available for the clinical management of BC, but limitations exist. It is difficult to surgically eliminate small lesions, while radiation and chemotherapy damage normal tissues, leading to severe side effects. Therefore, new approaches are required to improve the efficacy and specificity of BC treatment. Synthetic biology is a field emerging in the last decade that refers to biological elements, devices, and materials that are artificially synthesized according to users' needs. In this review, we discuss how to utilize genetic elements to regulate BC-related gene expression periodically and quantitatively to inhibit the initiation and progression of BC. In addition, the design and construction of gene circuits to distinguish cancer cells from normal cells to kill the former but spare the latter are elaborated. Then, we introduce the development of genetically modified T cells for targeted attacks on BC. Finally, synthetic nanomaterials specializing in detecting and killing BC cells are detailed. This review aims to describe the innovative details of the clinical diagnosis and treatment of BC from the perspective of synthetic biology.

P2RY2-AKT activation is a therapeutically actionable consequence of XPO1 inhibition in acute myeloid leukemia.

Selinexor is a first-in-class inhibitor of the nuclear exportin XPO1 that was recently approved by the US Food and Drug Administration for the treatment of multiple myeloma and diffuse large B-cell lymphoma. In relapsed/refractory acute myeloid leukemia (AML), selinexor has shown promising activity, suggesting that selinexor-based combination therapies may have clinical potential. Here, motivated by the hypothesis that selinexor's nuclear sequestration of diverse substrates imposes pleiotropic fitness effects on AML cells, we systematically catalog the pro- and anti-fitness consequences of selinexor treatment. We discover that selinexor activates PI3Kγ-dependent AKT signaling in AML by upregulating the purinergic receptor P2RY2. Inhibiting this axis potentiates the anti-leukemic effects of selinexor in AML cell lines, patient-derived primary cultures and multiple mouse models of AML. In a syngeneic, MLL-AF9-driven mouse model of AML, treatment with selinexor and ipatasertib outperforms both standard-of-care chemotherapy and chemotherapy with selinexor. Together, these findings establish drug-induced P2RY2-AKT signaling as an actionable consequence of XPO1 inhibition in AML.

Construction of a Macrophage Infiltration Regulatory Network and Related Prognostic Model of High-Grade Serous Ovarian Cancer.

BACKGROUND: High-grade serous ovarian cancer (HGSOC) carries the highest mortality in the gynecological cancers; however, therapeutic outcomes have not significantly improved in recent decades. Macrophages play an essential role in the occurrence and development of ovarian cancer, so the mechanisms of macrophage infiltration should be elucidated. METHOD: We downloaded transcriptome data of ovarian cancers from the Gene Expression Omnibus and The Cancer Genome Atlas. After rigorous screening, 1566 HGSOC were used for data analysis. CIBERSORT was used to estimate the level of macrophage infiltration and WGCNA was used to identify macrophage-related modules. We constructed a macrophage-related prognostic model using machine learning LASSO algorithm and verified it using multiple HGSOC cohorts. RESULTS: In the GPL570-OV cohort, high infiltration level of M1 macrophages was associated with a good outcome, while high infiltration level of M2 macrophages was associated with poor outcomes. We used WGCNA to select genes correlated with macrophage infiltration. These genes were used to construct protein-protein interaction maps of macrophage infiltration. IFL44L, RSAD2, IFIT3, MX1, IFIH1, IFI44, and ISG15 were the hub genes in the network. We then constructed a macrophage-related prognostic model composed of CD38, ACE2, BATF2, HLA-DOB, and WARS. The model had the ability to predict the overall survival rate of HGSOC patients in GPL570-OV, GPL6480-OV, TCGA-OV, GSE50088, and GSE26712. In exploring the immune microenvironment, we found that CD4 memory T cells and activated mast cells showed that the degree of infiltration was higher in the high-risk group, while M1 macrophages were the opposite, and HLA molecules were overexpressed in the high-risk group. CONCLUSION: We constructed a macrophage infiltration-related protein interaction network that provides a basis for studying macrophages in HGSOC. Our macrophage-related prognostic model is robust and widely applicable. It predicts overall survival in HGSOC patients and may improve HGSOC treatment.

OLFML2B Is a Robust Prognostic Biomarker in Bladder Cancer Through Genome-Wide Screening: A Study Based on Seven Cohorts.

BACKGROUND: Bladder cancer lacks useful and robust prognostic markers to stratify patients at risk. Our study is to identify a robust prognostic marker for bladder cancer. METHODS: The transcriptome and clinical data of bladder cancer were downloaded from multiple databases. We searched for genes with robust prognosis by Kaplan-Meier analysis of the whole genome. CIBERSORT and TIMER algorithm was used to calculate the degree of immune cell infiltration. RESULTS: We identified OLFML2B as a robust prognostic marker for bladder cancer in five cohorts. Kaplan-Meier analysis showed that patients with a high level of OLFML2B expression had a poor prognosis. The expression of OLFML2B increased with the increase of stage and grade. We found that patients with high expression of OLFML2B still had a poor prognosis in two small bladder cancer cohorts. OLFML2B also has the prognostic ability in ten other tumors, and the prognosis is poor in high expression. The correlation analysis between OLFML2B and immune cells showed that it was positively correlated with the degree of macrophage infiltration and highly co-expressed with tumor-associated macrophage markers. Finally, the Wound-healing assay and Colony formation assay results showed that the migration and proliferation ability of bladder cancer cell lines decreased after the knockdown of OLFML2B. CONCLUSIONS: In summary, OLFML2B is a robust risk prognostic marker, and it can help patients with bladder cancer improve individualized treatment.

Encapsulation of Lutein via Microfluidic Technology: Evaluation of Stability and In Vitro Bioaccessibility.

Inadequate intake of lutein is relevant to a higher risk of age-related eye diseases. However, lutein has been barely incorporated into foods efficiently because it is prone to degradation and is poorly bioaccessible in the gastrointestinal tract. Microfluidics, a novel food processing technology that can control fluid flows at the microscale, can enable the efficient encapsulation of bioactive compounds by fabricating suitable delivery structures. Hence, the present study aimed to evaluate the stability and the bioaccessibility of lutein that is encapsulated in a new noodle-like product made via microfluidic technology. Two types of oils (safflower oil (SO) and olive oil (OL)) were selected as a delivery vehicle for lutein, and two customized microfluidic devices (co-flow and combination-flow) were used. Lutein encapsulation was created by the following: (i) co-flow + SO, (ii) co-flow + OL, (iii) combination-flow + SO, and (iv) combination-flow + OL. The initial encapsulation of lutein in the noodle-like product was achieved at 86.0 ± 2.7%. Although lutein's stability experienced a decreasing trend, the retention of lutein was maintained above 60% for up to seven days of storage. The two types of device did not result in a difference in lutein bioaccessibility (co-flow: 3.1 ± 0.5%; combination-flow: 3.6 ± 0.6%) and SO and OL also showed no difference in lutein bioaccessibility (SO: 3.4 ± 0.8%; OL: 3.3 ± 0.4%). These results suggest that the types of oil and device do not affect the lutein bioaccessibility. Findings from this study may provide scientific insights into emulsion-based delivery systems that employ microfluidics for the encapsulation of bioactive compounds into foods.

ABL allosteric inhibitors synergize with statins to enhance apoptosis of metastatic lung cancer cells.

Targeting mitochondrial metabolism has emerged as a treatment option for cancer patients. The ABL tyrosine kinases promote metastasis, and enhanced ABL signaling is associated with a poor prognosis in lung adenocarcinoma patients. Here we show that ABL kinase allosteric inhibitors impair mitochondrial integrity and decrease oxidative phosphorylation. To identify metabolic vulnerabilities that enhance this phenotype, we utilized a CRISPR/Cas9 loss-of-function screen and identified HMG-CoA reductase, the rate-limiting enzyme of the mevalonate pathway and target of statin therapies, as a top-scoring sensitizer to ABL inhibition. Combination treatment with ABL allosteric inhibitors and statins decreases metastatic lung cancer cell survival in vitro in a synergistic manner. Notably, combination therapy in mouse models of lung cancer brain metastasis and therapy resistance impairs metastatic colonization with a concomitant increase in animal survival. Thus, metabolic combination therapy might be effective to decrease metastatic outgrowth, leading to increased survival for lung cancer patients with advanced disease.

Multidimensional Analyses of Tumor Immune Microenvironment Reveal the Possible Rationality of Immunotherapy and Identify High Immunotherapy Response Subtypes for Renal Papillary Cell Carcinoma.

Kidney renal papillary cell carcinoma (KIRP), the second most common subtype of renal cell carcinoma, still lacks effective treatment regimens for individualized immunotherapy because of the heterogeneity of its elusive immune microenvironment. Therefore, we aimed to comprehensively evaluate the immune microenvironment of KIRP by using the computational biology strategy to analyze the expression profile data of 289 KIRP patients obtained from The Cancer Genome Atlas database. Based on multidimensional, multi-omics bioinformatics analysis, we found that the tumor of patients with KIRP exhibited "hot" tumor characteristics but the CD8+ T cells in the tumor tissues did not limit tumor progression. Thus, patients with KIRP may realize higher clinical benefits by receiving treatment that can reverse CD8+ T-cell exhaustion. Among them, C1 and C3 immune subtypes could realize the best efficacy of reversing CD8+ T-cell exhaustion. Moreover, CCL5 and FASLG expression may be related to the formation of the immunosuppressive microenvironment in the tumors of patients with KIRP. In conclusion, the immune microenvironment landscape presented in this study provides a novel insight for further experimental and clinical exploration of tailored immunotherapy for patients with KIRP.

Evaluating the Velocity and Extent of Cortical Venous Filling in Patients With Severe Middle Cerebral Artery Stenosis or Occlusion.

Objective: To investigate the velocity and extent of cortical venous filling (CVF) and its association with clinical manifestations in patients with severe stenosis or occlusion of the middle cerebral artery (MCA) using dynamic computed tomography angiography (CTA). Methods: Fifty-eight patients (36 symptomatic and 22 asymptomatic) with severe unilateral stenosis (≥70%) or occlusion of the MCA M1 segment who underwent dynamic CTA were included. Collateral status, antegrade flow, and CVF of each patient were observed using dynamic CTA. Three types of cortical veins were selected to observe the extent of CVF, and the absence of CVF (CVF-) was recorded. Based on the appearance of CVF in the superior sagittal sinus, instances of CVF, including early (CVF1), peak (CVF2), and late (CVF3) venous phases, were recorded. The differences in CVF times between the affected and contralateral hemispheres were represented as rCVFs, and CVF velocity was defined compared to the median time of each rCVF. Results: All CVF times in the affected hemisphere were longer than those in the contralateral hemisphere (p < 0.05). Patients with symptomatic MCA stenosis had more ipsilateral CVF- (p = 0.02) and more delayed CVF at rCVF2 and rCVF21 (rCVF2-rCVF1) (p = 0.03 and 0.001, respectively) compared to those with asymptomatic MCA stenosis. For symptomatic patients, fast CVF at rCVF21 was associated with poor collateral status (odds ratio [OR] 6.42, 95% confidence interval [CI] 1.37-30.05, p = 0.02), and ipsilateral CVF- in two cortical veins was associated with poor 3-month outcomes (adjusted OR 0.025, 95% CI 0.002-0.33, p = 0.005). Conclusions: Complete and fast CVF is essential for patients with symptomatic MCA stenosis or occlusion. The clinical value of additional CVF assessment should be explored in future studies to identify patients with severe MCA stenosis or occlusion at a higher risk of stroke occurrence and poor recovery.

TRIB3 Promotes the Malignant Progression of Bladder Cancer: An Integrated Analysis of Bioinformatics and in vitro Experiments.

BACKGROUND: Bladder cancer is a common malignant tumor characterized by high mortality and high management costs; however, it lacks useful molecular prognostic markers. Tribbles pseudokinase 3 (TRIB3) is a pseudokinase that participates in cell tumor progression and metabolism and whose function in bladder cancer is not precisely known. MAIN METHODS: We downloaded transcriptome data and clinical data of bladder cancer from associated databases and extracted the expression matrix of TRIB3 for multiple bioinformatics analysis. RT-PCR detected the expression of TRIB3 in bladder cancer cells. After knockdown of TRIB3 with siRNA, we investigated TRIB3 function using CCK8, Cell Cycle and Transwell assays. KEY FINDINGS: Kaplan-Meier analysis of TRIB3 in the four cohorts showed that high expression of TRIB3 correlated with poor outcome. Expression of TRIB3 positively correlated with stage and grade and down-regulation of TRIB3 expression significantly inhibited proliferation, migration and cell cycle of bladder cancer cells. SIGNIFICANCE: TRIB3 is a potential prognostic marker and therapeutic target. It can be used to individualize the treatment of bladder cancer.

M2 Macrophage Co-Expression Factors Correlate With Immune Phenotype and Predict Prognosis of Bladder Cancer.

PURPOSE: Therapeutic targets of tumor-associated macrophages have been discovered and used clinically as immunotherapy. M2 macrophages are tumor-associated macrophages that promote cancer progression. This article explores the related factors and the effects of type M2 macrophages. METHOD: We obtained bladder cancer (BC) sequencing data from TCGA and GSE31189. We used the CIBERSORT algorithm calculate M2 macrophage proportions among 22 type immune cells. The Estimate package was used to measure BC purity. M2 macrophage-related genes were selected using WGCNA. Receiver operating characteristic curves and Kaplan-Meier analyses were performed to determine the risk score, conducted for M2 macrophage-related factors. The Pearson test was used to determine the correlation among M2 macrophage-related genes, clinical phenotype, immune phenotype and tumor mutation burden (TMB). The TIMER database was used to calculate correlations among M2 macrophages and other cancers. RESULTS: Expression of four M2 macrophages co-expressed genes (CD163, CD209, CSF1, MMD) positively correlated with infiltration of M2 macrophages, which were enriched in the negative regulation of immune system process and the positive regulation of tumor necrosis factor production. M2 macrophage-related factors are robust biomarkers for predicting the BC and immune phenotypes. The Cox regression model built on these four co-expression factors showed a close correlation with outcome (AUC = 0.64). The four co-expression factors negatively correlated outcome and TMB. CONCLUSION: Four co-expressed genes promote high levels of infiltration of type M2 macrophages in the negative regulation of immune system processes and the positive regulation of tumor necrosis factor production processes. These co-expressed genes and the biological process they involve might suggest new strategies for regulation of chemotaxis in M2 macrophages.

Macrophage M2 Co-expression Factors Correlate With the Immune Microenvironment and Predict Outcome of Renal Clear Cell Carcinoma.

Purpose: In the tumor microenvironment, the functional differences among various tumor-associated macrophages (TAM) are not completely clear. Tumor-associated macrophages are thought to promote the progression of cancer. This article focuses on exploring M2 macrophage-related factors and behaviors of renal clear cell carcinoma. Method: We obtained renal clear cell carcinoma data from TCGA-KIRC-FPKM, GSE8050, GSE12606, GSE14762, and GSE3689. We used the "Cibersort" algorithm to calculate type M2 macrophage proportions among 22 types of immune cells. M2 macrophage-related co-expression module genes were selected using weighted gene co-expression network analysis (WGCNA). A renal clear cell carcinoma prognosis risk score was built based on M2 macrophage-related factors. The ROC curve and Kaplan-Meier analysis were performed to evacuate the risk score in various subgroups. The Pearson test was used to calculate correlations among M2 macrophage-related genes, clinical phenotype, immune phenotype, and tumor mutation burden (TMB). We measured differences in co-expression of genes at the protein level in clear renal cell carcinoma tissues. Results: There were six M2 macrophage co-expressed genes (F13A1, FUCA1, SDCBP, VSIG4, HLA-E, TAP2) related to infiltration of M2 macrophages; these were enriched in neutrophil activation and involved in immune responses, antigen processing, and presentation of exogenous peptide antigen via MHC class I. M2-related factor frequencies were robust biomarkers for predicting the renal clear cell carcinoma patient clinical phenotype and immune microenvironment. The Cox regression model, built based on M2 macrophage-related factors, showed a close prognostic correlation (AUC = 0.78). The M2 macrophage-related prognosis model also performed well in various subgroups. Using western blotting, we found that VSIG4 protein expression levels were higher in clear renal cell carcinoma tissues than in normal tissues. Conclusion: These co-expressed genes were most related to the M2 macrophage phenotype. They correlated with the immune microenvironment and predicted outcomes of renal clear cell carcinoma. These co-expressed genes and the biological processes associated with them might provide the basis for new strategies to intervene via chemotaxis of M2 macrophages.

A global integrated analysis of UNC5C down-regulation in cancers: insights from mechanism and combined treatment strategy.

As the transmembrane receptor of Netrin-1, the tumor suppressor gene Unc-5 Netrin Receptor C (UNC5C) can trigger apoptosis. Although its tumor suppressor effects have been demonstrated in solid tumors such as colon cancer, there is still a lack of systematic research on its expression regulation mechanism. To address this need, we analyzed datasets from The Cancer Genome Atlas (TCGA) database, including multi-omics data for 32 types of cancers and 10,967 cases. Analysis of these data revealed a trend of significantly decreased UNC5C expression in 16 types of solid tumors. Additionally, low UNC5C expression is related to poor prognosis of five types of tumors and restoring the expression of UNC5C can effectively inhibit the proliferation potential of renal cancer cells. Promoter DNA methylation, chromatin remodeling-mediated epigenetic regulation, transcriptional inhibition, RNA-binding protein and miRNA-mediated post-transcriptional inhibition, genetic changes caused by deep deletion and truncated mutations, and ubiquitinating enzyme-mediated protein degradation can synergistically cause the down-regulation of UNC5C expression in solid tumors. This study is the first to analyze the comprehensive molecular mechanism of down-regulation of the tumor suppressor gene UNC5C from multiple dimensions using pan-cancer data. Our results suggest that analyses of gene expression regulation relying on computational biological methods may help guide the targeted therapy of tumor suppressor gene reactivation.