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.

Comparison of Outcomes between Stent Retriever Combined with Contact Aspiration and Contact Aspiration Alone in Patients without Hyperdense Artery Sign/Susceptibility Vessel Sign.

PURPOSE: To examine the relationship between hyperdense artery sign (HAS)/susceptibility vessel sign (SVS) and thrombus composition and evaluate the effect of HAS/SVS status on the association between first-line thrombectomy techniques and outcomes in patients with acute anterior circulation large vessel occlusion (LVO). MATERIALS AND METHODS: From January 2018 to June 2021, 103 consecutive patients with acute anterior circulation LVO (75 [63.1%] men; median age, 66 years) who underwent thrombectomy and for whom the removed clot was available for histological analyses were retrospectively reviewed. The presence of HAS and SVS was assessed on unenhanced computed tomography (CT) and susceptibility-weighted imaging, respectively. Association of first-line thrombectomy techniques (stent retriever [SR] combined with contact aspiration [CA] vs CA alone) with outcomes was assessed according to HAS/SVS status. RESULTS: Among the included patients, 55 (53.4%) were HAS/SVS-negative, and 69 (67.0%) underwent first-line SR + CA. Higher relative densities of fibrin/platelets (0.56 vs 0.51; P < .001) and lower relative densities of erythrocytes (0.32 vs 0.42; P < .001) were observed in HAS/SVS-negative patients compared with HAS/SVS-positive patients. First-line SR + CA was associated with reduced odds of distal embolization (adjusted odds ratio, 0.18; 95% CI, 0.04-0.83; P = .027) and a more favorable 90-day functional outcome (adjusted odds ratio, 5.29; 95% CI, 1.06-26.34; P = .042) in HAS/SVS-negative patients and a longer recanalization time (53 vs 25 minutes; P = .025) and higher risk of subarachnoid hemorrhage (24.2% vs 0%; P = .044) in HAS/SVS-positive patients. CONCLUSIONS: Absence of HAS/SVS may indicate a higher density of fibrin/platelets in the thrombus, and first-line SR + CA yielded superior functional outcomes than CA alone in patients with acute LVO without HAS/SVS.

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.

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.

A robust 11-genes prognostic model can predict overall survival in bladder cancer patients based on five cohorts.

BACKGROUND: Bladder cancer is the tenth most common cancer globally, but existing biomarkers and prognostic models are limited. METHOD: In this study, we used four bladder cancer cohorts from The Cancer Genome Atlas and Gene Expression Omnibus databases to perform univariate Cox regression analysis to identify common prognostic genes. We used the least absolute shrinkage and selection operator regression to construct a prognostic Cox model. Kaplan-Meier analysis, receiver operating characteristic curve, and univariate/multivariate Cox analysis were used to evaluate the prognostic model. Finally, a co-expression network, CIBERSORT, and ESTIMATE algorithm were used to explore the mechanism related to the model. RESULTS: A total of 11 genes were identified from the four cohorts to construct the prognostic model, including eight risk genes (SERPINE2, PRR11, DSEL, DNM1, COMP, ELOVL4, RTKN, and MAPK12) and three protective genes (FABP6, C16orf74, and TNK1). The 11-genes model could stratify the risk of patients in all five cohorts, and the prognosis was worse in the group with a high-risk score. The area under the curve values of the five cohorts in the first year are all greater than 0.65. Furthermore, this model's predictive ability is stronger than that of age, gender, grade, and T stage. Through the weighted co-expression network analysis, the gene module related to the model was found, and the key genes in this module were mainly enriched in the tumor microenvironment. B cell memory showed low infiltration in high-risk patients. Furthermore, in the case of low B cell memory infiltration and high-risk score, the prognosis of the patients was the worst. CONCLUSION: The proposed 11-genes model is a promising biomarker for estimating overall survival in bladder cancer. This model can be used to stratify the risk of bladder cancer patients, which is beneficial to the realization of individualized treatment.

Predictive accuracy of markers or risk scores for interval censored survival data.

Methods for the evaluation of the predictive accuracy of biomarkers with respect to survival outcomes subject to right censoring have been discussed extensively in the literature. In cancer and other diseases, survival outcomes are commonly subject to interval censoring by design or due to the follow up schema. In this article, we present an estimator for the area under the time-dependent receiver operating characteristic (ROC) curve for interval censored data based on a nonparametric sieve maximum likelihood approach. We establish the asymptotic properties of the proposed estimator and illustrate its finite-sample properties using a simulation study. The application of our method is illustrated using data from a cancer clinical study. An open-source R package to implement the proposed method is available on Comprehensive R Archive Network.

fastJT: An R package for robust and efficient feature selection for machine learning and genome-wide association studies.

BACKGROUND: Parametric feature selection methods for machine learning and association studies based on genetic data are not robust with respect to outliers or influential observations. While rank-based, distribution-free statistics offer a robust alternative to parametric methods, their practical utility can be limited, as they demand significant computational resources when analyzing high-dimensional data. For genetic studies that seek to identify variants, the hypothesis is constrained, since it is typically assumed that the effect of the genotype on the phenotype is monotone (e.g., an additive genetic effect). Similarly, predictors for machine learning applications may have natural ordering constraints. Cross-validation for feature selection in these high-dimensional contexts necessitates highly efficient computational algorithms for the robust evaluation of many features. RESULTS: We have developed an R extension package, fastJT, for conducting genome-wide association studies and feature selection for machine learning using the Jonckheere-Terpstra statistic for constrained hypotheses. The kernel of the package features an efficient algorithm for calculating the statistics, replacing the pairwise comparison and counting processes with a data sorting and searching procedure, reducing computational complexity from O(n2) to O(n log(n)). The computational efficiency is demonstrated through extensive benchmarking, and example applications to real data are presented. CONCLUSIONS: fastJT is an open-source R extension package, applying the Jonckheere-Terpstra statistic for robust feature selection for machine learning and association studies. The package implements an efficient algorithm which leverages internal information among the samples to avoid unnecessary computations, and incorporates shared-memory parallel programming to further boost performance on multi-core machines.

Efficient estimation of grouped survival models.

BACKGROUND: Time- and dose-to-event phenotypes used in basic science and translational studies are commonly measured imprecisely or incompletely due to limitations of the experimental design or data collection schema. For example, drug-induced toxicities are not reported by the actual time or dose triggering the event, but rather are inferred from the cycle or dose to which the event is attributed. This exemplifies a prevalent type of imprecise measurement called grouped failure time, where times or doses are restricted to discrete increments. Failure to appropriately account for the grouped nature of the data, when present, may lead to biased analyses. RESULTS: We present groupedSurv, an R package which implements a statistically rigorous and computationally efficient approach for conducting genome-wide analyses based on grouped failure time phenotypes. Our approach accommodates adjustments for baseline covariates, and analysis at the variant or gene level. We illustrate the statistical properties of the approach and computational performance of the package by simulation. We present the results of a reanalysis of a published genome-wide study to identify common germline variants associated with the risk of taxane-induced peripheral neuropathy in breast cancer patients. CONCLUSIONS: groupedSurv enables fast and rigorous genome-wide analysis on the basis of grouped failure time phenotypes at the variant, gene or pathway level. The package is freely available under a public license through the Comprehensive R Archive Network.

bcSeq: an R package for fast sequence mapping in high-throughput shRNA and CRISPR screens.

Summary: CRISPR-Cas9 and shRNA high-throughput sequencing screens have abundant applications for basic and translational research. Methods and tools for the analysis of these screens must properly account for sequencing error, resolve ambiguous mappings among similar sequences in the barcode library in a statistically principled manner, and be computationally efficient. Herein we present bcSeq, an open source R package that implements a fast and parallelized algorithm for mapping high-throughput sequencing reads to a barcode library while tolerating sequencing error. The algorithm uses a Trie data structure for speed and resolves ambiguous mappings by using a statistical sequencing error model based on Phred scores for each read. Availability and implementation: The package source code and an accompanying tutorial are available at http://bioconductor.org/packages/bcSeq/. Supplementary information: Supplementary data are available at Bioinformatics online.

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.

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.

Molecular simulation of the effect of water content on CO2, CH4, and N2 adsorption characteristics of coal.

The objective of this work was to investigate the sorption behavior of gases, namely CO2, CH4, and N2, by molecules of coal sampled from Linglu mine under different water inclusion rates. To this end, the adsorption, diffusion, adsorption heat, and potential energy distribution characteristics of the gases in the coal pores at different water inclusion rates were analyzed using molecular dynamics and grand canonical ensemble Monte Carlo methods. The results showed that the adsorption relationship of the coal molecules on CO2, CH4, and N2 exhibited a downtrend followed by an uptrend when the water content was increased from 0 to 3.6%. The adsorption amount of CO2 was approximately twice as much as those of CH4 and N2, indicating that the competitive adsorption advantage of CO2 compared with those of CH4 and N2 was unaffected by the water content. The trend in the average heat of adsorption was generally consistent with the trend in the density of coal molecules under different moisture contents. Under the same conditions, the diffusion coefficient within a coal molecule was negatively related to the water content in the system. The layer spacing of the water molecules (2.875 Å) was greater than the liquid-water layer spacing, indicating the formation of a water molecule layer at this point, which inhibited gas adsorption. This study lays a theoretical foundation for further investigating the microscopic mechanism of coal-water interaction.

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.

Antibiotic use attenuates response to immune checkpoint blockade in urothelial carcinoma via inhibiting CD74-MIF/COPA: revealing cross-talk between anti-bacterial immunity and anti-tumor immunity through a tumor marker prognostic study.

BACKGROUND: Immune checkpoint blockade (ICB) has emerged as a promising therapy for both resectable urothelial carcinoma (UC) patients preparing for radical surgery and unresectable UC patients, whereas the objective response rate of ICB remains unsatisfactory due to various factors. Antibiotic (ATB) use can influence intra-tumoral bacteria, which may further reduce ICB efficacy. The study aims to evaluate the effects of ATB use on prognosis and response in UC patients undergoing ICB, and explore potential molecular mechanisms of ATBs and intra-tumoral bacteria impacting UC immune microenvironment. MATERIALS AND METHODS: Pooled analyses, synthesizing evidence from 12 studies and 3496 UC patients with ICB treatment, was conducted via a meta-analysis. In addition, single-cell RNA and single-cell microbiome data were analyzed based on eight UC samples and 63185 single cells. Bulk RNA sequencing and clinical data from a single-arm, multi-center, atezolizumab-treated, phase 2 trial, IMvigor210, were used for validation. The study is registered at PROSPERO (XXX) and at Research Registry (XXX). RESULTS: ATB use exhibited worse overall survival (HR=1.46, 95%CI=[1.20, 1.77], P<0.001, heterogeneity I²=51%) and lower objective response (OR=0.43, 95%CI=[0.27, 0.68], P<0.001, heterogeneity I²=0%) in UC patients receiving ICB. Single-cell transcriptome and single-cell microbiome analyses identified the presence of intra-tumoral bacteria was obviously related to elevated anti-bacterial immune functions; and anti-bacterial immunity was positively correlated to anti-tumor immunity in UC immune microenvironment. Intra-tumoral bacteria could up-regulate CD74-MIF/COPA signaling of immune cells and activation of CD74-MIF/COPA mediated the promotion of T cell anti-tumor function induced by anti-bacterial immune cells. UC patients with higher CD74-MIF/COPA signaling carried better overall survival (HR=1.60, 95%CI=[1.19, 2.15], P=0.002) in IMvigor210 immunotherapy cohort. CONCLUSION: ATB use reduces overall survival and objective response to ICB in UC patients. Anti-bacterial immune cell functions induced by intra-cellular bacteria in UC microenvironment might up-regulate the function of anti-tumor T immune cells via activating CD74-MIF/COPA, whereas ATB could inhibit the above process through killing intra-cellular bacteria and result in poorer clinical benefit of ICB. The use of ATB should be considered carefully during neoadjuvant immunotherapy period for resectable UC patients preparing for radical surgery and during immunotherapy period for unresectable UC patients.

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.

Tension trapping of carbonyl ylides facilitated by a change in polymer backbone.

Epoxidized polybutadiene and epoxidized polynorbornene were subjected to pulsed ultrasound in the presence of small molecules capable of being trapped by carbonyl ylides. When epoxidized polybutadiene was sonicated, there was no observable small molecule addition to the polymer. Concurrently, no appreciable isomerization (cis to trans epoxide) was observed, indicating that the epoxide rings along the backbone are not mechanically active under the experimental conditions employed. In contrast, when epoxidized polynorbornene was subjected to the same conditions, both addition of ylide trapping reagents and net isomerization of cis to trans epoxide were observed. The results demonstrate the mechanical activity of epoxides, show that mechanophore activity is determined not only by the functional group but also the polymer backbone in which it is embedded, and facilitate a characterization of the reactivity of the ring-opened dialkyl epoxide.

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.

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.