The development of targeted chemotherapeutic agents against colorectal cancer (CRC), one of the most common cancers with a high mortality rate, is in a constant need. Nannocystins are a family of myxobacterial secondary metabolites featuring a 21-membered depsipeptide ring. The in vitro anti-CRC activity of natural and synthetic nannocystins was well documented, but little is known about their in vivo efficacy and if positive, the underlying mechanism of action. In this study we synthesized a nitroaromatic nannocystin through improved preparation of a key fragment, and characterized its in vitro activity and in vivo efficacy against CRC. We first described the total synthesis of compounds 2-4 featuring Heck macrocyclization to forge their 21-membered macrocycle. In a panel of 7 cancer cell lines from different tissues, compound 4 inhibited the cell viability with IC values of 1-6 nM. In particular, compound 4 (1, 2, 4 nM) inhibited the proliferation of CRC cell lines (HCT8, HCT116 and LoVo) in both concentration and time dependent manners. Furthermore, compound 4 concentration-dependently inhibited the colony formation and migration of CRC cell lines. Moreover, compound 4 induced cell cycle arrest at sub-G phase, apoptosis and cellular senescence in CRC cell lines. In three patient-derived CRC organoids, compound 4 inhibited the PDO with IC values of 3.68, 28.93 and 11.81 nM, respectively. In a patient-derived xenograft mouse model, injection of compound 4 (4, 8 mg/kg, i.p.) every other day for 12 times dose-dependently inhibited the tumor growth without significant change in body weight. We conducted RNA-sequencing, molecular docking and cellular thermal shift assay to elucidate the anti-CRC mechanisms of compound 4, and revealed that it exerted its anti-CRC effect at least in part by targeting AKT1.
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http://dx.doi.org/10.1038/s41401-024-01231-w | DOI Listing |
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Zentalis Pharmaceuticals, Inc., San Diego, CA, USA.
Upregulation of Cyclin E1 and subsequent activation of CDK2 accelerates cell cycle progression from G1 to S phase and is a common oncogenic driver in gynecological malignancies. WEE1 kinase counteracts the effects of Cyclin E1/CDK2 activation by regulating multiple cell cycle checkpoints. Here we characterized the relationship between Cyclin E1/CDK2 activation and sensitivity to the selective WEE1 inhibitor azenosertib.
View Article and Find Full Text PDFSci Rep
January 2025
School of Medicine, Nankai University, Tianjin, 300071, China.
Cholangiocarcinoma (CCA), a highly aggressive form of cancer, is known for its high mortality rate. A Disintegrin and Metalloprotease Domain-like Protein Decysin-1 (ADAMDEC1) can promote the development and metastasis in various tumors by degrading the extracellular matrix. However, its regulatory mechanism in CCA remains unclear.
View Article and Find Full Text PDFAnn Hematol
January 2025
Department of Hematology, Navy Medical Center of PLA, Naval Medical University, No. 338 West Huaihai Road, Changning District, Shanghai, 200052, China.
Multiple myeloma(MM) remains incurable with high relapse and chemoresistance rates. Differentially expressed genes(DEGs) between newly diagnosed myeloma and secondary plasma cell leukemia(sPCL) were subjected to a weighted gene co-expression network analysis(WGCNA). Drug resistant myeloma cell lines were established.
View Article and Find Full Text PDFSci Rep
January 2025
School of Physics, Engineering and Technology, University of York, Heslington, York, YO10 5DD, UK.
Prostate cancer is a disease which poses an interesting clinical question: Should it be treated? Only a small subset of prostate cancers are aggressive and require removal and treatment to prevent metastatic spread. However, conventional diagnostics remain challenged to risk-stratify such patients; hence, new methods of approach to biomolecularly sub-classify the disease are needed. Here we use an unsupervised self-organising map approach to analyse live-cell Raman spectroscopy data obtained from prostate cell-lines; our aim is to exemplify this method to sub-stratify, at the single-cell-level, the cancer disease state using high-dimensional datasets with minimal preprocessing.
View Article and Find Full Text PDFNat Commun
January 2025
Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
Spatial protein expression technologies can map cellular content and organization by simultaneously quantifying the expression of >40 proteins at subcellular resolution within intact tissue sections and cell lines. However, necessary image segmentation to single cells is challenging and error prone, easily confounding the interpretation of cellular phenotypes and cell clusters. To address these limitations, we present STARLING, a probabilistic machine learning model designed to quantify cell populations from spatial protein expression data while accounting for segmentation errors.
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