The road to death: Caspases, cleavage, and pores

Synthesis and biological evaluation of novel isatin-phenol hybrids as potential antitumor agents

Chemotherapy was one of indispensable methods for treating cancer, and the development of novel antitumor drugs was necessary due to the emergent drug resistance and undesirable side effects. In the current study, we successfully constructed a novel library of isatin-phenol hybrids by chemical coupling of isatin (1) with a series of active phenols including honokiol (2), magnolol (3), bis(4-hydroxy-3-methylphenyl) sulfide (4), bisphenol A (5), carvacrol (6), and hydroxyqunioline (7) respectively. The target molecules were screened for anticancer activity, and we further investigate the anti-cancer mechanism of the most potent compound IPH10 in vitro and in vivo. Animal experiments demonstrated that IPH10 possessed strong anti-tumor effects in vivo without hepatic and renal toxicity. Moreover, the effects of IPH10 on mitochondrial membrane potential (JC-1) and reactive oxygen species (ROS) in tumor cells were investigated, and the results showed that IPH10 could significantly increase the content of ROS and dramatically decrease the mitochondrial membrane potential in tumor cells. Furthermore, the effect of IPH10 on apoptotic proteins in tumor cells was also explored by Western blotting analysis, which revealed that IPH10 could significantly increase the protein content of cleaved caspase-9/cleaved caspase-3/cleaved caspase-7/cleaved PARP. Taken together, the current study reported a promising novel chemotherapeutic drug candidate IPH10 that could inhibit the growth and induce the apoptosis of tumor cells.

m6A modification of lncRNA ABHD11-AS1 promotes colorectal cancer progression and inhibits ferroptosis through TRIM21/IGF2BP2/ FOXM1 positive feedback loop

Long non-coding RNA (lncRNA) is closely related to a variety of human cancers, which may provide huge potential biomarkers for cancer diagnosis and treatment. However, the aberrant expression of most lncRNAs in colorectal cancer (CRC) remains elusive. This study aims to explore the clinical significance and potential mechanism of lncRNA ABHD11 antisense RNA 1 (ABHD11-AS1) in the colorectal cancer. Here, we demonstrated that lncRNA ABHD11-AS1 is high-expressed in colorectal cancer (CRC) patients, and strongly related with poor prognosis. Functionally, ABHD11-AS1 suppresses ferroptosis and promotes proliferation and migration in CRC both in vitro and in vivo. Mechanically, lncRNA ABHD11-AS1 interacted with insulin-like growing factor 2 mRNA-binding protein 2 (IGF2BP2) to enhance FOXM1 stability, forming an ABHD11-AS1/FOXM1 positive feedback loop. E3 ligase tripartite motif containing 21 (TRIM21) promotes the degradation of IGF2BP2 via the K48-ubiquitin-lysosome pathway and ABHD11-AS1 promotes the interaction between IGF2BP2 and TRIM21 as scaffold platform. Furthermore, N6 -adenosine-methyltransferase-like 3 (METTL3) upregulated the stabilization of ABHD11-AS1 through the m6A reader IGF2BP2. Our study highlights ABHD11-AS1 as a significant regulator in CRC and it may become a potential target in future CRC treatment.

Association of TRAIL receptor with phosphatase SHP-1 enables repressing T cell receptor signaling and T cell activation through inactivating Lck

BACKGROUND

T cell receptor (TCR) signaling and T cell activation are tightly regulated by gatekeepers to maintain immune tolerance and avoid autoimmunity. The TRAIL receptor (TRAIL-R) is a TNF-family death receptor that transduces apoptotic signals to induce cell death. Recent studies have indicated that TRAIL-R regulates T cell-mediated immune responses by directly inhibiting T cell activation without inducing apoptosis; however, the distinct signaling pathway that regulates T cell activation remains unclear. In this study, we screened for intracellular TRAIL-R-binding proteins within T cells to explore the novel signaling pathway transduced by TRAIL-R that directly inhibits T cell activation.

METHODS

Whole-transcriptome RNA sequencing was used to identify gene expression signatures associated with TRAIL-R signaling during T cell activation. High-throughput screening with mass spectrometry was used to identify the novel TRAIL-R binding proteins within T cells. Co-immunoprecipitation, lipid raft isolation, and confocal microscopic analyses were conducted to verify the association between TRAIL-R and the identified binding proteins within T cells.

RESULTS

TRAIL engagement downregulated gene signatures in TCR signaling pathways and profoundly suppressed phosphorylation of TCR proximal tyrosine kinases without inducing cell death. The tyrosine phosphatase SHP-1 was identified as the major TRAIL-R binding protein within T cells, using high throughput mass spectrometry-based proteomics analysis. Furthermore, Lck was co-immunoprecipitated with the TRAIL-R/SHP-1 complex in the activated T cells. TRAIL engagement profoundly inhibited phosphorylation of Lck (Y394) and suppressed the recruitment of Lck into lipid rafts in the activated T cells, leading to the interruption of proximal TCR signaling and subsequent T cell activation.

CONCLUSIONS

TRAIL-R associates with phosphatase SHP-1 and transduces a unique and distinct immune gatekeeper signal to repress TCR signaling and T cell activation via inactivating Lck. Thus, our results define TRAIL-R as a new class of immune checkpoint receptors for restraining T cell activation, and TRAIL-R/SHP-1 axis can serve as a potential therapeutic target for immune-mediated diseases.

Gasdermin E dictates inflammatory responses by controlling the mode of neutrophil death

Both lytic and apoptotic cell death remove senescent and damaged cells in living organisms. However, they elicit contrasting pro- and anti-inflammatory responses, respectively. The precise cellular mechanism that governs the choice between these two modes of death remains incompletely understood. Here we identify Gasdermin E (GSDME) as a master switch for neutrophil lytic pyroptotic death. The tightly regulated GSDME cleavage and activation in aging neutrophils are mediated by proteinase-3 and caspase-3, leading to pyroptosis. GSDME deficiency does not alter neutrophil overall survival rate; instead, it specifically precludes pyroptosis and skews neutrophil death towards apoptosis, thereby attenuating inflammatory responses due to augmented efferocytosis of apoptotic neutrophils by macrophages. In a clinically relevant acid-aspiration-induced lung injury model, neutrophil-specific deletion of GSDME reduces pulmonary inflammation, facilitates inflammation resolution, and alleviates lung injury. Thus, by controlling the mode of neutrophil death, GSDME dictates host inflammatory outcomes, providing a potential therapeutic target for infectious and inflammatory diseases.

ProsperousPlus: a one-stop and comprehensive platform for accurate protease-specific substrate cleavage prediction and machine-learning model construction

Proteases contribute to a broad spectrum of cellular functions. Given a relatively limited amount of experimental data, developing accurate sequence-based predictors of substrate cleavage sites facilitates a better understanding of protease functions and substrate specificity. While many protease-specific predictors of substrate cleavage sites were developed, these efforts are outpaced by the growth of the protease substrate cleavage data. In particular, since data for 100+ protease types are available and this number continues to grow, it becomes impractical to publish predictors for new protease types, and instead it might be better to provide a computational platform that helps users to quickly and efficiently build predictors that address their specific needs. To this end, we conceptualized, developed, tested and released a versatile bioinformatics platform, ProsperousPlus, that empowers users, even those with no programming or little bioinformatics background, to build fast and accurate predictors of substrate cleavage sites. ProsperousPlus facilitates the use of the rapidly accumulating substrate cleavage data to train, empirically assess and deploy predictive models for user-selected substrate types. Benchmarking tests on test datasets show that our platform produces predictors that on average exceed the predictive performance of current state-of-the-art approaches. ProsperousPlus is available as a webserver and a stand-alone software package at http://prosperousplus.unimelb-biotools.cloud.edu.au/.