Unveiling the immune symphony: decoding colorectal cancer metastasis through immune interactions

Colorectal cancer (CRC), known for its high metastatic potential, remains a leading cause of cancer-related death. This review emphasizes the critical role of immune responses in CRC metastasis, focusing on the interaction between immune cells and tumor microenvironment. We explore how immune cells, through cytokines, chemokines, and growth factors, contribute to the CRC metastasis cascade, underlining the tumor microenvironment’s role in shaping immune responses. The review addresses CRC’s immune evasion tactics, especially the upregulation of checkpoint inhibitors like PD-1 and CTLA-4, highlighting their potential as therapeutic targets. We also examine advanced immunotherapies, including checkpoint inhibitors and immune cell transplantation, to modify immune responses and enhance treatment outcomes in CRC metastasis. Overall, our analysis offers insights into the interplay between immune molecules and the tumor environment, crucial for developing new treatments to control CRC metastasis and improve patient prognosis, with a specific focus on overcoming immune evasion, a key aspect of this special issue

Carbapenem-resistant Citrobacter freundii harboring blaKPC−2 and blaNDM−1: a study on their transferability and potential dissemination via generating a transferrable hybrid plasmid mediated by IS6100

IntroductionThe increase in clinical Enterobacteriaceae with dual carbapenemase has become a serious healthcare concern. It is essential to characterize the transferability and potential dissemination of blaKPC−2- and blaNDM−1-coharboring carbapenem-resistant Citrobacter freundii (CRCF).MethodsFour blaKPC−2- and blaNDM−1-coharboring CRCF strains were collected from our surveillance of the prevalence of carbapenem-resistant Enterobacteriaceae. The isolates were assessed using species identification, antimicrobial susceptibility testing, conjugation assays, whole-genome sequencing, plasmid stability, and fitness costs. Clonality, genome, plasmidome, and phylogeny were analyzed to reveal potential dissemination.ResultsThree ST523 blaKPC−2- and blaNDM−1-coharboring CRCF strains, collected from the same hospital within 1 month, exhibited high homology (both identity and coverage >99%), implying clonal dissemination and a small-scale outbreak. Moreover, the blaKPC−2 and blaNDM−1 genes were coharbored on an IncR plasmid, probably generated by a blaKPC−2-harboring plasmid acquiring blaNDM−1, in these three strains. Importantly, the IncR plasmid may form a transferable hybrid plasmid, mediated by IS6100 via transposition, with another IncFII plasmid included in the same C. freundii strain. Furthermore, the blaKPC−2 and blaNDM−1 of the fourth CRCF strain are located on two different non-transferable plasmids lacking complete transfer elements. Additionally, throughout the course of the 10-day continuous passage, the genetic surroundings of blaNDM−1 in four CRCF strains were gradually excised from their plasmids after the 8th day, whereas they maintained 100% retention for blaKPC−2. Genome and plasmidome analyses revealed that blaKPC−2- or blaNDM−1-harboring C. freundii were divergent, and these plasmids have high homology to plasmids of other Enterobacteriaceae.ConclusionClonal dissemination of ST523 blaKPC−2- and blaNDM−1-coharboring CRCF strains was detected, and we first reported blaKPC−2 and blaNDM−1 concomitantly located on one plasmid, which could be transferred with mediation by IS6100 via transposition. Continued surveillance should urgently be implemented

Heat shock protein 90 promotes RNA helicase DDX5 accumulation and exacerbates hepatocellular carcinoma by inhibiting autophagy

Objective: Hepatocellular carcinoma (HCC), the main type of liver cancer, has a high morbidity and mortality, and a poor prognosis. RNA helicase DDX5, which acts as a transcriptional co-regulator, is overexpressed in most malignant tumors and promotes cancer cell growth. Heat shock protein 90 (HSP90) is an important molecular chaperone in the conformational maturation and stabilization of numerous proteins involved in cell growth or survival. Methods: DDX5 mRNA and protein expression in surgically resected HCC tissues from 24 Asian patients were detected by quantitative real-time PCR and Western blot, respectively. The interaction of DDX5-HSP90 was determined by molecular docking, immunoprecipitation, and laser scanning confocal microscopy. The autophagy signal was detected by Western blot. The cell functions and signaling pathways of DDX5 were determined in 2 HCC cell lines. Two different murine HCC xenograft models were used to determine the function of DDX5 and the therapeutic effect of an HSP90 inhibitor. Results: HSP90 interacted directly with DDX5 and inhibited DDX5 protein degradation in the AMPK/ULK1-regulated autophagy pathway. The subsequent accumulation of DDX5 protein induced the malignant phenotype of HCC by activating the β-catenin signaling pathway. The silencing of DDX5 or treatment with HSP90 inhibitor both blocked in vivo tumor growth in a murine HCC xenograft model. High levels of HSP90 and DDX5 protein were associated with poor prognoses. Conclusions: HSP90 interacted with DDX5 protein and subsequently protected DDX5 protein from AMPK/ULK1-regulated autophagic degradation. DDX5 and HSP90 are therefore potential therapeutic targets for HCC

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery