Metal- and Base-Free Radical Cascade Cyclization/Hydrolysis of CN-Containing 1,6-Enynes with Ethers to Access Polyheterocycles.

A convenient and straightforward approach for the radical cascade cyclization/hydrolysis of CN-containing 1,6-enynes with simple ethers under metal- and base-free conditions is described. This strategy provides a variety of valuable ethers-substituted polyheterocycles via the construction of three C-C bonds, one C=O bond, and two new six-membered rings within a single procedure. The resulting products can smoothly undergo follow-up conversions to various useful scaffolds. The methodology shows excellent functional group tolerance, high step- and atom- economy, and mild reaction conditions, which can be further scaled up to gram quantity in a satisfactory yield.

High baseline tumor burden-associated macrophages promote an immunosuppressive microenvironment and reduce the efficacy of immune checkpoint inhibitors through the IGFBP2-STAT3-PD-L1 pathway.

BACKGROUND: Several clinical studies have uncovered a negative correlation between baseline tumor burden and the efficacy of immune checkpoint inhibitor (ICI) treatment. This study aimed to uncover the specific mechanisms underlying the difference in sensitivity to ICI treatment between tumors with high (HTB) and low (LTB) tumor burden. METHODS: For in vivo studies, several mouse models of subcutaneous tumors were established, and transcriptome sequencing, immunohistochemistry, and flow cytometry assays were used to detect the immune status in these subcutaneous tumors. For in vitro experiments, co-culture models, cytokine antibody arrays, western blotting, flow cytometry, and enzyme-linked immunosorbent assays were used to explore the underlying molecular mechanisms RESULTS: We found that MC38 or B16 subcutaneous tumors from the HTB group did not show any response to anti-programmed cell death protein-1 (PD-1) therapy. Through flow cytometry assays, we found that the infiltration with CD8+ T cells was significantly decreased whereas M2-like macrophages were enriched in subcutaneous tumors of HTB groups compared with those of LTB group. These changes were not affected by the initial number of injected tumor cells or tumor age, nor could they be reversed by surgical tumor reduction. Intraperitoneal colony-stimulating factor 1 receptor (CSF-1R) inhibitor PLX3397 injection at different time points of tumor growth only had an effect when administered in the early tumor stage to maintain the "heat" of the tumor microenvironment during the process of tumor growth, thereby achieving a response to ICI treatment when the tumor grew to a large size. Mechanistically, we found that insulin-like growth factor binding protein 2 (IGFBP2) expression levels were significantly elevated in HTB tumor tissues. IGFBP2 promoted the programmed death-ligand 1 (PD-L1) expression in M2-like macrophages by activating signal transducer and activator of transcription 3 (STAT3), and PD-L1+ M2-like macrophages exerted an immunosuppressive effect by inhibiting the proliferation and activation of CD8+ T cells in a PD-L1-dependent fashion. CONCLUSIONS: This study suggested that the low efficacy of ICI treatment in HTB tumors is mainly attributed to the intratumoral accumulation of PD-L1+ M2-like macrophages via the IGFBP2-STAT3-PD-L1 signaling pathway and their substantial inhibitory effects on T cell proliferation and activation.

Matrix Stiffness Triggers Lipid Metabolic Cross-talk between Tumor and Stromal Cells to Mediate Bevacizumab Resistance in Colorectal Cancer Liver Metastases.

Bevacizumab is an anti-VEGF monoclonal antibody that plays an important role in the combination treatment of advanced colorectal cancer. However, resistance remains a major hurdle limiting bevacizumab efficacy, highlighting the importance of identifying a mechanism of antiangiogenic therapy resistance. Here, we investigated biophysical properties of the extracellular matrix (ECM) related to metabolic processes and acquired resistance to bevacizumab. Evaluation of paired pre- and posttreatment samples of liver metastases from 20 colorectal cancer patients treated with combination bevacizumab therapy, including 10 responders and 10 nonresponders, indicated that ECM deposition in liver metastases and a highly activated fatty acid oxidation (FAO) pathway were elevated in nonresponders after antiangiogenic therapy compared with responders. In mouse models of liver metastatic colorectal cancer (mCRC), anti-VEGF increased ECM deposition and FAO in colorectal cancer cells, and treatment with the FAO inhibitor etomoxir enhanced the efficacy of antiangiogenic therapy. Hepatic stellate cells (HSC) were essential for matrix stiffness-mediated FAO in colon cancer cells. Matrix stiffness activated lipolysis in HSCs via the focal adhesion kinase (FAK)/yes-associated protein (YAP) pathway, and free fatty acids secreted by HSCs were absorbed as metabolic substrates and activated FAO in colon cancer cells. Suppressing HSC lipolysis using FAK and YAP inhibition enhanced the efficacy of anti-VEGF therapy. Together, these results indicate that bevacizumab-induced ECM remodeling triggers lipid metabolic cross-talk between colon cancer cells and HSCs. This metabolic mechanism of bevacizumab resistance mediated by the physical tumor microenvironment represents a potential therapeutic target for reversing drug resistance. SIGNIFICANCE: Extracellular matrix stiffening drives bevacizumab resistance by stimulating hepatic stellate cells to provide fuel for mCRC cells in the liver, indicating a potential metabolism-based therapeutic strategy for overcoming resistance.

UIF: An Objective Quality Assessment for Underwater Image Enhancement.

Due to complex and volatile lighting environment, underwater imaging can be readily impaired by light scattering, warping, and noises. To improve the visual quality, Underwater Image Enhancement (UIE) techniques have been widely studied. Recent efforts have also been contributed to evaluate and compare the UIE performances with subjective and objective methods. However, the subjective evaluation is time-consuming and uneconomic for all images, while existing objective methods have limited capabilities for the newly-developed UIE approaches based on deep learning. To fill this gap, we propose an Underwater Image Fidelity (UIF) metric for objective evaluation of enhanced underwater images. By exploiting the statistical features of these images in CIELab space, we present the naturalness, sharpness, and structure indexes. Among them, the naturalness and sharpness indexes represent the visual improvements of enhanced images; the structure index indicates the structural similarity between the underwater images before and after UIE. We combine all indexes with a saliency-based spatial pooling and thus obtain the final UIF metric. To evaluate the proposed metric, we also establish a first-of-its-kind large-scale UIE database with subjective scores, namely Underwater Image Enhancement Database (UIED). Experimental results confirm that the proposed UIF metric outperforms a variety of underwater and general-purpose image quality metrics. The database and source code are available at https://github.com/z21110008/UIF.

Embedding Regularizer Learning for Multi-View Semi-Supervised Classification.

Classification remains challenging when confronted with the existence of multi-view data with limited labels. In this paper, we propose an embedding regularizer learning scheme for multi-view semi-supervised classification (ERL-MVSC). The proposed framework integrates diversity, sparsity and consensus to dexterously manipulate multi-view data with limited labels. To encourage diversity, ERL-MVSC recasts a linear regression model to derive view-specific embedding regularizers and automatically determines their weights. This is able to tactfully incorporate complementary information of different views. To ensure sparsity, ERL-MVSC imposes l2,1 -norm on a fused embedding regularizer to exploit the sparse local structure of samples, thereby conveying valuable classification information and enhancing the robustness against noise/outliers. To enhance consensus, ERL-MVSC learns a shared predicted label matrix, which serves as the comment target of multi-view classification. With these techniques, we formulate ERL-MVSC as a joint optimization problem of an embedding regularizer and a predicted label matrix, which can be solved by a coordinate descent method. Extensive experimental results on real-world datasets demonstrate the effectiveness and superiority of the proposed algorithm.

Recent Advances in Copper-Catalyzed C-N Bond Formation Involving N-Centered Radicals.

C-N bonds are pervasive throughout organic-based materials, natural products, pharmaceutical compounds, and agricultural chemicals. Considering the widespread importance of C-N bonds, the development of greener and more convenient ways to form C-N bonds, especially in late-stage synthesis, has become one of the hottest research goals in synthetic chemistry. Copper-catalyzed radical reactions involving N-centered radicals have emerged as a sustainable and promising approach to build C-N bonds. As a chemically popular and diverse radical species, N-centered radicals have been used for all kinds of reactions for C-N bond formation by taking advantage of their inherently incredible reactive flexibility. Copper is also the most abundant and economic catalyst with the most relevant activity for facilitating the synthesis of valuable compounds. Therefore, the aim of the present Review was to illustrate recent and significant advances in C-N bond formation methods and to understand the unique advantages of copper catalysis in the generation of N-centered radicals since 2016. To provide an ease of understanding for the readers, this Review was organized based on the types of nitrogen sources (amines, amides, sulfonamides, oximes, hydrazones, azides, and tert-butyl nitrite).

Recent Progress in Understanding the Action of Natural Compounds at Novel Therapeutic Drug Targets for the Treatment of Liver Cancer.

Liver cancer is the third most common cause of cancer-related death following lung and stomach cancers. As a highly lethal disease, liver cancer is diagnosed frequently in less developed countries. Natural compounds extracted from herbs, animals and natural materials have been adopted by traditional Chinese medicine (TCM) practices and reported to be effective in the development of new medications for the treatment of diseases. It is important to focus on the mechanisms of action of natural compounds against hepatocellular carcinoma (HCC), particularly in terms of cell cycle regulation, apoptosis induction, autophagy mediation and cell migration and invasion. In this review, we characterize novel representative natural compounds according to their pharmacologic effects based on recently published studies. The aim of this review is to summarize and explore novel therapeutic drug targets of natural compounds, which could accelerate the discovery of new anticancer drugs.

CRIP1 cooperates with BRCA2 to drive the nuclear enrichment of RAD51 and to facilitate homologous repair upon DNA damage induced by chemotherapy.

Homologous recombination (HR) repair is an important determinant of chemosensitivity. However, the mechanisms underlying HR regulation remain largely unknown. Cysteine-rich intestinal protein 1 (CRIP1) is a member of the LIM/double-zinc finger protein family and is overexpressed and associated with prognosis in several tumor types. However, to date, the functional role of CRIP1 in cancer biology is poorly understood. Here we found that CRIP1 downregulation causes HR repair deficiency with concomitant increase in cell sensitivity to cisplatin, epirubicin, and the poly ADP-ribose polymerase (PARP) inhibitor olaparib in gastric cancer cells. Mechanistically, upon DNA damage, CRIP1 is deubiquitinated and upregulated by activated AKT signaling. CRIP1, in turn, promotes nuclear enrichment of RAD51, which is a prerequisite step for HR commencement, by stabilizing BRCA2 to counteract FBXO5-targeted RAD51 degradation and by binding to the core domain of RAD51 (RAD51184-257) in coordination with BRCA2, to facilitate nuclear export signal masking interactions between BRCA2 and RAD51. Moreover, through mass spectrometry screening, we found that KPNA4 is at least one of the carriers controlling the nucleo-cytoplasmic distribution of the CRIP1-BRCA2-RAD51 complex in response to chemotherapy. Consistent with these findings, RAD51 inhibitors block the CRIP1-mediated HR process, thereby restoring chemotherapy sensitivity of gastric cancer cells with high CRIP1 expression. Analysis of patient specimens revealed an abnormally high level of CRIP1 expression in GC tissues compared to that in the adjacent normal mucosa and a significant negative association between CRIP1 expression and survival time in patient cohorts with different types of solid tumors undergoing genotoxic treatments. In conclusion, our study suggests an essential function of CRIP1 in promoting HR repair and facilitating gastric cancer cell adaptation to genotoxic therapy.

Gene expression. MicroRNA control of protein expression noise.

MicroRNAs (miRNAs) repress the expression of many genes in metazoans by accelerating messenger RNA degradation and inhibiting translation, thereby reducing the level of protein. However, miRNAs only slightly reduce the mean expression of most targeted proteins, leading to speculation about their role in the variability, or noise, of protein expression. We used mathematical modeling and single-cell reporter assays to show that miRNAs, in conjunction with increased transcription, decrease protein expression noise for lowly expressed genes but increase noise for highly expressed genes. Genes that are regulated by multiple miRNAs show more-pronounced noise reduction. We estimate that hundreds of (lowly expressed) genes in mouse embryonic stem cells have reduced noise due to substantial miRNA regulation. Our findings suggest that miRNAs confer precision to protein expression and thus offer plausible explanations for the commonly observed combinatorial targeting of endogenous genes by multiple miRNAs, as well as the preferential targeting of lowly expressed genes.