Prostate cancer (PCa) patients who progress to metastatic castration-resistant PCa (mCRPC) mostly have poor outcomes due to the lack of effective therapies. Our recent study established the orphan nuclear receptor ROR γ as a novel therapeutic target for CRPC. Here, we reveal that elaiophylin (Elai), an antibiotic from Actinomycete streptomyces , is a novel ROR γ antagonist and showed potent antitumor activity against CRPC in vitro and in vivo . We demonstrated that Elai selectively binded to ROR γ protein and potently blocked ROR γ transcriptional regulation activities. Structure–activity relationship studies showed that Elai occupied the binding pocket with several key interactions. Furthermore, Elai markedly reduced the recruitment of ROR γ to its genomic DNA response element (RORE), suppressed the expression of ROR γ target genes AR and AR variants, and significantly inhibited PCa cell growth. Importantly, Elai strongly suppressed tumor growth in both cell line based and patient-derived PCa xenograft models. Taken together, these results suggest that Elai is novel therapeutic ROR γ inhibitor that can be used as a drug candidate for the treatment of human CRPC.
The majority of lncRNAs’ roles in tumor immunology remain elusive. This project performed a CRISPR activation screening of 9744 lncRNAs in melanoma cells cocultured with human CD8 + T cells. We identified 16 lncRNAs potentially regulating tumor immune response. Further integrative analysis using tumor immunogenomics data revealed that IL10RB-DT and LINC01198 are significantly correlated with tumor immune response and survival in melanoma and breast cancer. Specifically, IL10RB-DT suppresses CD8 + T cells activation via inhibiting IFN-γ–JAK–STAT1 signaling and antigen presentation in melanoma and breast cancer cells. On the other hand, LINC01198 ’s up-regulation sensitizes the killing of tumor cells by CD8 + T cells. Mechanistically, LINC01198 interacts and activates NF-κB component p65 to trigger the type I and type II interferon responses in melanoma and breast cancer cells. Our study systematically characterized novel lncRNAs involved in tumor immune response.
Background: Pooled CRISPR screen is a promising tool in drug targets or essential genes identification with the utilization of three different systems including CRISPR knockout (CRISPRko), CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa). Aside from continuous improvements in technology, more and more bioinformatics methods have been developed to analyze the data obtained by CRISPR screens which facilitate better understanding of physiological effects. Results: Here, we provide an overview on the application of CRISPR screens and bioinformatics approaches to analyzing different types of CRISPR screen data. We also discuss mechanisms and underlying challenges for the analysis of dropout screens, sorting-based screens and single-cell screens. Conclusion: Different analysis approaches should be chosen based on the design of screens. This review will help community to better design novel algorithms and provide suggestions for wet-lab researchers to choose from different analysis methods.
Currently, the calculation of the surface roughness parameter is mainly based on the surface height data of the rectangular region, which results in the nonrectangular relay contact surface topography acquisition being limited to a certain local area, and it is difficult to characterize the overall topography state of contacts. In this paper, a method of fitting the rotation roughness parameter is proposed, which is to fit the roughness parameter of the largest inscribed square of contact surface under different rotation angles, and finally, a comprehensive roughness parameter value characterizing the whole circular contact surface is obtained. The Tamura feature analysis method is used to calculate the rotation roughness parameters of the circular contact at various angles. The effective area for calculating the surface roughness of circular contacts is increased from 63.66 to 99.14%. By calculating the moving Hurst index, the rotation roughness parameters of each angle are proven to conform to the fractional Brownian motion, and the rotation roughness parameters are fitted accordingly. Finally, the validity of the fitting parameters is verified by a neural network, which provides a feasible method for comprehensively characterizing the overall topography of circular contact. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
Cancer treatments such as chemotherapies may change or accelerate aging trajectories in cancer patients. Emerging evidence has shown that “omics” data can be used to study molecular changes of the aging process. Here, we integrated the drug-induced and normal aging transcriptomic data to computationally characterize the potential cancer drug-induced aging process in patients. Our analyses demonstrated that the aging-associated gene expression in the GTEx dataset can recapitulate the well-established aging hallmarks. We next characterized the drug-induced transcriptomic changes of 28 FDA approved cancer drugs in brain, kidney, muscle, and adipose tissues. Further drug-aging interaction analysis identified 34 potential drug regulated aging events. Those events include aging accelerating effects of vandetanib (Caprelsa®) and dasatinib (Sprycel®) in brain and muscle, respectively. Our result also demonstrated aging protective effect of vorinostat (Zolinza®), everolimus (Afinitor®), and bosutinib (Bosulif®) in brain.
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