Palladium-Copper-Catalyzed Oxidative Intermolecular [2 + 2 + 2] Coupling-Annulation: Regioselective Synthesis of Multiaryl-Substituted Benzenes.

A palladium-catalyzed intermolecular [2 + 2 + 2] oxidative coupling-annulation of terminal alkenes and alkynes using copper(II) as the oxidant has been developed through direct C-C bond formation. These reactions provide effective access to multiaryl-substituted benzenes with high regioselectivity in the absence of any ligands. The features of this protocol are broad substrate scope, and high atom and step economy. The aggregation-induced emission properties of selected products were further investigated. These synthesized multiaryl-substituted benzenes may be worth exploring for further applications in the fields of advanced functional materials or drugs.

Multi-omics landscape analysis reveals the pan-cancer association of arginine biosynthesis genes with tumor immune evasion and therapy resistance.

Background: The metabolism of arginine, a conditionally essential amino acid, plays a crucial role in cancer progression and prognosis. However, a more detailed understanding of the influence of arginine biosynthesis genes in cancer is currently unavailable. Methods: We performed an integrative multi-omics analysis using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to determine the characteristics of these genes across multiple cancer types. To measure the overall activity of arginine biosynthesis genes in cancer, we calculated arginine biosynthesis scores based on gene expression. Results: Our results indicated that the arginine biosynthesis score was negatively correlated with immune-related pathways, immune infiltration, immune checkpoint expression, and patient prognosis, and single-cell data further clarified that patients with high arginine biosynthesis scores showed a reduced proportion of T and B cells in an immune desert tumor microenvironment and were insensitive to immunotherapy. We also identified several potential drugs through the Cancer Therapeutic Response Portal (CTRP) and Genomics of Drug Sensitivity in Cancer (GDSC) databases that could target arginine biosynthesis genes and potentially improve the response rate to immunotherapy in patients with a high arginine biosynthesis fraction. Conclusion: Overall, our analyses emphasize that arginine biosynthesis genes are associated with immune evasion in several cancers. Targeting these genes may facilitate more effective immunotherapy.

Visible Light Mediated Chemoselective Hydroxylation of Benzylic Methylenes.

We have developed a metal-free photocatalytic selective hydroxylation of benzylic methylenes to secondary alcohols. This approach utilizes low-cost eosin Y as photocatalyst, O2 as green oxidant, and inexpensive triethylamine as inhibitor for overoxidation. The mild reaction conditions enable the production of secondary alcohols with 56-95% yields, making it a promising and environmental-friendly method for the synthesis of secondary alcohols from benzylic methylenes.

HES4 is a potential biomarker for bladder cancer: a Mendelian randomization study.

Background: Patients with bladder cancer (BLCA) have a poor prognosis and little progress has been made in treatment. Therefore, the purpose of this work was to employ Mendelian randomization (MR) and transcriptome analysis to identify a novel biomarker that could be used to reliably diagnose BLCA. Methods: TCGA-BLCA and GSE121711 datasets were obtained from public databases. Genome-wide association study (GWAS) data of BLCA outcome (373,295 samples containing 9,904,926 single nucleotide polymorphisms) were obtained through the IEU OpenGWAS database. Differentially expressed genes were applied as exposure factors, and MR analysis was performed to identify genes that had a causal relationship with BLCA. Then, the patients were divided into high and low expression groups according to the expression levels of candidate genes, and genes with survival differences were identified. Univariate and multivariate Cox regression were used to investigate the prognostic value of the expression of these genes. A nomogram was constructed based on independent prognostic factors, and we analyzed the functions and pathways associated with the identified genes as well as their relationship with the immune microenvironment. Results: HES4 was identified as a biomarker. HES4 status, age, and stage were identified as independent prognostic factors, and an excellent nomogram was established. Bioinformatic analysis suggested that HES4 might be associated with the activation of the immune response, bone development, and cancer pathways. The BLCA samples were divided into high and low HES4 groups. The stromal score and 33 immune cells were remarkably different between the two groups, with HES4 expression being negatively correlated with macrophages and mast cells, and positively correlated with eosinophils and central memory CD4+ T cells. Finally, HES4 was up-regulated in cancer samples in both TCGA-BLCA and GSE121711 datasets. Conclusion: This study identified HES4 as an independent prognostic factor for BLCA outcome based on MR and transcriptome analysis, which provides useful information for future research on and treatment of BLCA.

Development of a stemness-related prognostic index to provide therapeutic strategies for bladder cancer.

Bladder cancer (BC) is a heterogeneous disease with varying clinical outcomes. Recent evidence suggests that cancer progression involves the acquisition of stem-like signatures, and assessing stemness indices help uncover patterns of intra-tumor molecular heterogeneity. We used the one-class logistic regression algorithm to compute the mRNAsi for each sample in BLCA cohort. We subsequently classified BC patients into two subtypes based on 189 mRNAsi-related genes, using the unsupervised consensus clustering. Then, we identified nine hub genes to construct a stemness-related prognostic index (SRPI) using Cox regression, LASSO regression and Random Forest methods. We further validated SRPI using two independent datasets. Afterwards, we examined the molecular and immune characterized of SRPI. Finally, we conducted multiply drug screening and experimental approaches to identify and confirm the most proper agents for patients with high SRPI. Based on the mRNAsi-related genes, BC patients were classified into two stemness subtypes with distinct prognosis, functional annotations, genomic variations and immune profiles. Using the SRPI, we identified a specific subgroup of BC patients with high SRPI, who had a poor response to immunotherapy, and were less sensitive to commonly used chemotherapeutic agents, FGFR inhibitors, and EGFR inhibitors. We further identified that dasatinib was the most promising therapeutic agent for this subgroup of patients. This study provides further insights into the stemness classification of BC, and demonstrates that SRPI is a promising tool for predicting prognosis and therapeutic opportunities for BC patients.

LASS2 enhances chemosensitivity to cisplatin by inhibiting PP2A-mediated ß-catenin dephosphorylation in a subset of stem-like bladder cancer cells.

BACKGROUND: The benefits of first-line, cisplatin-based chemotherapy for muscle-invasive bladder cancer are limited due to intrinsic or acquired resistance to cisplatin. Increasing evidence has revealed the implication of cancer stem cells in the development of chemoresistance. However, the underlying molecular mechanisms remain to be elucidated. This study investigates the role of LASS2, a ceramide synthase, in regulating Wnt/ß-catenin signaling in a subset of stem-like bladder cancer cells and explores strategies to sensitize bladder cancer to cisplatin treatment. METHODS: Data from cohorts of our center and published datasets were used to evaluate the clinical characteristics of LASS2. Flow cytometry was used to sort and analyze bladder cancer stem cells (BCSCs). Tumor sphere formation, soft agar colony formation assay, EdU assay, apoptosis analysis, cell viability, and cisplatin sensitivity assay were used to investigate the functional roles of LASS2. Immunofluorescence, immunoblotting, coimmunoprecipitation, LC-MS, PCR array, luciferase reporter assays, pathway reporter array, chromatin immunoprecipitation, gain-of-function, and loss-of-function approaches were used to investigate the underlying mechanisms. Cell- and patient-derived xenograft models were used to investigate the effect of LASS2 overexpression and a combination of XAV939 on cisplatin sensitization and tumor growth. RESULTS: Patients with low expression of LASS2 have a poorer response to cisplatin-based chemotherapy. Loss of LASS2 confers a stem-like phenotype and contributes to cisplatin resistance. Overexpression of LASS2 results in inhibition of self-renewal ability of BCSCs and increased their sensitivity to cisplatin. Mechanistically, LASS2 inhibits PP2A activity and dissociates PP2A from ß-catenin, preventing the dephosphorylation of ß-catenin and leading to the accumulation of cytosolic phospho-ß-catenin, which decreases the transcription of the downstream genes ABCC2 and CD44 in BCSCs. Overexpression of LASS2 combined with a tankyrase inhibitor (XAV939) synergistically inhibits tumor growth and restores cisplatin sensitivity. CONCLUSIONS: Targeting the LASS2 and ß-catenin pathways may be an effective strategy to overcome cisplatin resistance and inhibit tumor growth in bladder cancer patients.

Integrating Bulk and Single-Cell RNA Sequencing Reveals Heterogeneity, Tumor Microenvironment, and Immunotherapeutic Efficacy Based on Sialylation-Related Genes in Bladder Cancer.

Background: As known abnormal sialylation exerts crucial roles in the growth, metastasis, and immune evasion of cancers, but the molecular characteristics and roles in bladder cancer (BLCA) remain unclear. This study intends to establish BLCA risk stratification based on sialylation-related genes and elucidate its role in prognosis, tumor microenvironment, and immunotherapy of BLCA. Methods: Bulk RNA-seq and scRNA-seq data were downloaded from open-access databases. The scRNA-seq data were processed using the R package "Seurat" to identify the core cell types. The tumor sub-typing of BLCA samples was performed by the R package "ConsensusClusterPlus" in the bulk RNA-seq data. Signature genes were identified by the R package "limma" and univariate regression analysis to calculate risk scores using the R package "GSVA" and establish risk stratification of BLCA patients. Finally, the differences in clinicopathological characteristics, tumor microenvironment, and immunotherapy efficacy between the different groups were investigated. Results: 5 core cell types were identified in the scRNA-seq dataset, with monocytes and macrophages presenting the greatest percentage, sialylation-related gene expression, and sialylation scores. The bulk RNA-seq samples were classified into 3 tumor subtypes based on 19 prognosis-related sialylation genes. The 10 differential expressed genes (DEGs) with the smallest p-values were collected as signature genes, and the risk score was calculated, with the samples divided into high and low-risk score groups. The results showed that patients in the high-risk score group exhibited worse survival outcomes, higher tumor grade, more advanced stage, more frequency of gene mutations, higher expression levels of immune checkpoints, and lower immunotherapy response. Conclusion: We established a novel risk stratification of BLCA from a glycomics perspective, which demonstrated good accuracy in determining the prognostic outcome, clinicopathological characteristics, immune microenvironment, and immunotherapy efficacy of patients, and we are proposing to apply it to direct the choice of clinical treatment options for patients.

Prognosis analysis and validation of lipid metabolism-associated lncRNAs and tumor immune microenvironment in bladder cancer.

BACKGROUND: Numerous types of research revealed that long noncoding RNAs (lncRNAs) played a significant role in immune response and the tumor microenvironment of bladder cancer (BLCA). Dysregulated lipid metabolism is considered to be one of the major risk factors for BLCA, the study aimed to detect the lipid metabolism-related lncRNAs (LMRLs) along with their potential prognostic values and immune correlations in BLCA. METHODS: We collected lipid metabolism-related genes, expression profiles, and clinical information on BLCA from the Molecular Signature Database (MSigDB) and the TCGA database, respectively. Differentially expressed lipid metabolism genes (DE-LMRGs) and differentially expressed long non-coding RNAs (DE-lncRNAs) were selected using the limma package. Spearman correlation analysis was employed to explore the correlations between DE-lncRNAs and DE-LMRGs and to further develop protein-protein interaction (PPI) networks and perform mutational analysis. The least absolute shrinkage and selection operator (LASSO) and univariate Cox analysis were then employed to construct a prognostic risk model. The performance of the model was evaluated using Kaplan-Meier survival analysis, receiver operating characteristic (ROC) curves, and consistency indices. In addition, we downloaded the GSE31684 dataset for external validation of the prognostic signature. Moreover, we explored the association of the risk model with immune cell infiltration and chemotherapy response analysis to reveal the tumor immune microenvironment of BLCA. Finally, RT-qPCR was utilized to validate the expression of prognostic genes. RESULTS: A total of 48 DE-LncRNAs and 33 DE-LMRGs were found to be robustly correlated, and were used to construct a lncRNA-mRNA co-expression network, in which ACACB, ACOX2, and BCHE showed high mutation rates. Then, a risk model based on three LMRLs (RP11-465B22.8, MIR100HG, and LINC00865) was constructed. The risk model effectively distinguished between the clinical outcomes of BLCA patients, with high-risk scores indicating a worse prognosis and with substantial prognostic prediction accuracy. The model's results were consistent in the GSE31684 dataset. In addition, a nomogram was constructed based on the risk score, age, pathological T-stage, and pathological N-stage, which showed robust predictive power. Immune landscape analysis indicated that the risk model was significantly associated with T-cell CD4 memory activation, M1 macrophage, M2 macrophage, dendritic cell activation, and T-cell regulatory. We predicted that 49 drugs would perform satisfactorily in the high-risk group. Additionally, we found five m6A regulators associated with the high- and low-risk groups, suggesting that upstream regulation of LncRNA could be a novel target for BLCA treatment. Finally, RT-qPCR showed that RP11-465B22.8 was highly expressed in BLCA, while MIR100HG and LINC00865 were downregulated in BLCA. CONCLUSION: Our findings suggest that the three LMRLs may serve as potential prognostic and immunotherapeutic biomarkers in BLCA. In addition, our study provides new ideas for understanding the pathogenic mechanisms and developing therapeutic strategies for BLCA patients.

Comprehensive analysis of scRNA-Seq and bulk RNA-Seq reveals dynamic changes in the tumor immune microenvironment of bladder cancer and establishes a prognostic model.

BACKGROUND: The prognostic management of bladder cancer (BLCA) remains a great challenge for clinicians. Recently, bulk RNA-seq sequencing data have been used as a prognostic marker for many cancers but do not accurately detect core cellular and molecular functions in tumor cells. In the current study, bulk RNA-seq and single-cell RNA sequencing (scRNA-seq) data were combined to construct a prognostic model of BLCA. METHODS: BLCA scRNA-seq data were downloaded from Gene Expression Omnibus (GEO) database. Bulk RNA-seq data were obtained from the UCSC Xena. The R package "Seurat" was used for scRNA-seq data processing, and the uniform manifold approximation and projection (UMAP) were utilized for downscaling and cluster identification. The FindAllMarkers function was used to identify marker genes for each cluster. The limma package was used to obtain differentially expressed genes (DEGs) affecting overall survival (OS) in BLCA patients. Weighted gene correlation network analysis (WGCNA) was used to identify BLCA key modules. The intersection of marker genes of core cells and genes of BLCA key modules and DEGs was used to construct a prognostic model by univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO) analyses. Differences in clinicopathological characteristics, immune microenvironment, immune checkpoints, and chemotherapeutic drug sensitivity between the high and low-risk groups were also investigated. RESULTS: scRNA-seq data were analyzed to identify 19 cell subpopulations and 7 core cell types. The ssGSEA showed that all 7 core cell types were significantly downregulated in tumor samples of BLCA. We identified 474 marker genes from the scRNA-seq dataset, 1556 DEGs from the Bulk RNA-seq dataset, and 2334 genes associated with a key module identified by WGCNA. After performing intersection, univariate Cox, and LASSO analysis, we obtained a prognostic model based on the expression levels of 3 signature genes, namely MAP1B, PCOLCE2, and ELN. The feasibility of the model was validated by an internal training set and two external validation sets. Moreover, patients with high-risk scores are predisposed to experience poor OS, a larger prevalence of stage III-IV, a greater TMB, a higher infiltration of immune cells, and a lesser likelihood of responding favorably to immunotherapy. CONCLUSION: By integrating scRNA-seq and bulk RNA-seq data, we constructed a novel prognostic model to predict the survival of BLCA patients. The risk score is a promising independent prognostic factor that is closely correlated with the immune microenvironment and clinicopathological characteristics.

Enantioselective rhodium-catalyzed addition of arylboronic acids to N-heteroaryl ketones: synthesis of α-hydroxy acids.

The enantioselective addition of arylboronic acids to N-heteroaryl ketones provides a convenient access to chiral α-heteroaryl tertiary alcohols, yet addition reactions of this type have been challenging due to catalyst deactivation. In this report, an efficient rhodium-catalyzed addition of arylboronic acids to N-heteroaryl ketones is established, affording a variety of valuable α-heteroaryl alcohols with excellent functional group compatibility. The employment of the WingPhos ligand containing two anthryl groups is crucial for this transformation. In particular, a range of chiral benzoxazolyl-substituted tertiary alcohols were formed with excellent ee values and yields by employing a Rh loading as low as 0.3 mol%, which can serve as a practical protocol to furnish a series of chiral α-hydroxy acids after hydrolysis.

Differential expression of slow and fast-repriming tetrodotoxin-sensitive sodium currents in dorsal root ganglion neurons.

Sodium channel Nav1.7 triggers the generation of nociceptive action potentials and is important in sending pain signals under physiological and pathological conditions. However, studying endogenous Nav1.7 currents has been confounded by co-expression of multiple sodium channel isoforms in dorsal root ganglion (DRG) neurons. In the current study, slow-repriming (SR) and fast-repriming (FR) tetrodotoxin-sensitive (TTX-S) currents were dissected electrophysiologically in small DRG neurons of both rats and mice. Three subgroups of small DRG neurons were identified based on the expression pattern of SR and FR TTX-S currents. A majority of rat neurons only expressed SR TTX-S currents, while a majority of mouse neurons expressed additional FR TTX-S currents. ProTx-II inhibited SR TTX-S currents with variable efficacy among DRG neurons. The expression of both types of TTX-S currents was higher in Isolectin B4-negative (IB4-) compared to Isolectin B4-positive (IB4+) neurons. Paclitaxel selectively increased SR TTX-S currents in IB4- neurons. In simulation experiments, the Nav1.7-expressing small DRG neuron displayed lower rheobase and higher frequency of action potentials upon threshold current injections compared to Nav1.6. The results suggested a successful dissection of endogenous Nav1.7 currents through electrophysiological manipulation that may provide a useful way to study the functional expression and pharmacology of endogenous Nav1.7 channels in DRG neurons.

A novel prognostic model based on three integrin subunit genes-related signature for bladder cancer.

Background: Presently, a comprehensive analysis of integrin subunit genes (ITGs) in bladder cancer (BLCA) is absent. This study endeavored to thoroughly analyze the utility of ITGs in BLCA through computer algorithm-based bioinformatics. Methods: BLCA-related materials were sourced from reputable databases, The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). R software-based bioinformatics analyses included limma-differential expression analysis, survival-Cox analysis, glmnet-Least absolute shrinkage and selection operator (LASSO), clusterProfiler-functional annotation, and gsva-estimate-immune landscape analysis. The expression difference of key genes was verified by quantitative real-time polymerase chain reaction (qRT-PCR). Results: Among the 11 ITGs that were abnormally expressed in BLCA, ITGA7, ITGA5, and ITGB6 were categorized as the optimal variables for structuring the risk model. The high-risk subcategories were typified by brief survival, abysmal prognosis, prominent immune and stromal markers, and depressed tumor purity. The risk model was also an isolated indicator of the impact of clinical outcomes in BLCA patients. Moreover, the risk model, specifically the high-risk subcategory with inferior prognosis, became heavily interlinked with the immune-inflammatory response and smooth muscle contraction and relaxation. Conclusion: This study determined three ITGs with prognostic values (ITGA7, ITGA5, and ITGB6), composed a novel (ITG-associated) prognostic gene signature, and preliminarily probed the latent molecular mechanisms of the model.

Passage number affects differentiation of sensory neurons from human induced pluripotent stem cells.

Induced pluripotent stem cells (iPSCs) are a valuable resource for neurological disease-modeling and drug discovery due to their ability to differentiate into neurons reflecting the genetics of the patient from which they are derived. iPSC-derived cultures, however, are highly variable due to heterogeneity in culture conditions. We investigated the effect of passage number on iPSC differentiation to optimize the generation of sensory neurons (iPSC-dSNs). Three iPSC lines reprogrammed from the peripheral blood of three donors were differentiated into iPSC-dSNs at passage numbers within each of the following ranges: low (5-10), intermediate (20-26), and high (30-38). Morphology and pluripotency of the parent iPSCs were assessed prior to differentiation. iPSC-dSNs were evaluated based on electrophysiological properties and expression of key neuronal markers. All iPSC lines displayed similar morphology and were similarly pluripotent across passage numbers. However, the expression levels of neuronal markers and sodium channel function analyses indicated that iPSC-dSNs differentiated from low passage numbers better recapitulated the sensory neuron phenotype than those differentiated from intermediate or high passage numbers. Our results demonstrate that lower passage numbers may be better suited for differentiation into peripheral sensory neurons.

Prostate sclerosing adenopathy: A clinicopathological and immunohistochemical study of twelve patients.

BACKGROUND: Although sclerosing adenopathy of the prostate is a very rare benign disease, an effective differential diagnosis is required. Here, we report the clinicopathological and immunohistochemical morphological features of 12 cases of sclerosing adenopathy of the prostate to improve understanding of the disease. AIM: To investigate the clinicopathological features, diagnosis, and immunohistochemical phenotypes that distinguish prostate sclerosing adenopathy from other conditions. METHODS: The clinical data, laboratory tests, pathological morphology, and immunohistochemical phenotypes of 12 cases of prostatic sclerosing adenopathy were retrospectively analyzed, and the relevant literature was reviewed. RESULTS: All patients were elderly men (mean age, 71.7 years; 62-83 years). Eleven of them had hematuria, urinary frequency, urinary urgency, difficulty in urination, and serum total prostate-specific antigen values within the normal range. One patient had increased blood pressure. Enlarged prostates with single to multiple calcifying foci were observed. Moreover, prostate tissue hyperplastic changes were observed in all patients. Small follicular hyperplastic nodules without an obvious envelope, with a growth pattern mimicking the infiltration pattern of "prostate adenocarcinoma" were noted. Basal cells expressed AR, CKH, P63, and CK5/6, and myoepithelial markers, such as calponin, S100, and smooth muscle actin. No recurrence or exacerbation of the lesions was observed, except for one case of death due to bladder cancer. CONCLUSION: Prostatic sclerosing adenopathy is highly misdiagnosed as prostate adenocarcinoma or other tumor-like lesions. Therefore, it should attract the attention of clinicopathologic researchers.

A terahertz near-field nanoscopy revealing edge fringes with a fast and highly sensitive quantum-well photodetector.

We demonstrate the successful implementation of a terahertz (THz) quantum-well photodetector (QWP) for effective signal collection in a scattering-type scanning near-field optical microscope (s-SNOM) system. The light source is an electrically pumped THz quantum cascade laser (QCL) at 4.2 THz, which spectrally matches with the peak photoresponse of THz QWP. The sensitive THz QWP has a low noise equivalent power (NEP) of about 1.1 pW/Hz0.5 and a spectral response range from 2 to 7 THz. The fast-responding capability of the THz QWP is vital for detecting the rapidly tip-modulated THz light which can effectively suppress the background noise. The THz images of the nanostructure demonstrate a spatial resolution of about 95 nm, corresponding to ∼λ/752 at 4.2 THz. We experimentally investigate and theoretically interpret the formation of the fringes which appear at the edge position of a gold stripe in the THz near-field image.