Targeted α-particle-emitting radionuclides have great potential for the treatment of a broad range of cancers at different stages of progression. A platform that accurately measures cancer cellular sensitivity to α-particle irradiation could guide and accelerate clinical translation. Here, we performed high-content profiling of cellular survival following exposure to α-particles emitted from radium-223 (Ra) using 28 genetically diverse human tumor cell lines. Significant variation in cellular sensitivity across tumor cells was observed. Ra was significantly more potent than sparsely ionizing irradiation, with a median relative biological effectiveness of 10.4 (IQR: 8.4-14.3). Cells that are the most resistant to γ radiation, such as gain-of-function mutant cells, were sensitive to α-particles. Combining these profiling results with genetic features, we identified several somatic copy-number alterations, gene mutations, and the basal expression of gene sets that correlated with radiation survival. Activating mutations in , a frequent event in cancer, decreased sensitivity to Ra. The identification of cellular and genetic determinants of sensitivity to Ra may guide the clinical incorporation of targeted α-particle emitters in the treatment of several cancer types. SIGNIFICANCE: These findings address limitations in the preclinical guidance and prediction of radionuclide tumor sensitivity by identifying intrinsic cellular and genetic determinants of cancer cell survival following exposure to α-particle irradiation..
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http://dx.doi.org/10.1158/0008-5472.CAN-19-0859 | DOI Listing |
NPJ Precis Oncol
January 2025
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
Department of Laboratory Medicine, Karolinska Institutet, ANA Futura, Alfred Nobels Allé 8, Floor 8, 14152, Huddinge, Sweden.
ITK-SYK and TEL-SYK (also known as ETV6-SYK) are human tumor-causing chimeric proteins containing the kinase region of SYK, and the membrane-targeting, N-terminal, PH-TH domain-doublet of ITK or the dimerizing SAM-PNT domain of TEL, respectively. ITK-SYK causes peripheral T cell lymphoma, while TEL-SYK was reported in myelodysplastic syndrome. BTK is a kinase highly related to ITK and to further delineate the role of the N-terminus, we generated the corresponding fusion-kinase BTK-SYK.
View Article and Find Full Text PDFActa Neuropathol Commun
January 2025
Department of Neurology, Peking Union Medical College Hospital, Peking Union Medical College (PUMC) and Chinese Academy of Medical Science (CAMS), Beijing, China.
Mutations in the ANXA11 gene, encoding an RNA-binding protein, have been implicated in the pathogenesis of amyotrophic lateral sclerosis (ALS), but the underlying in vivo mechanisms remain unclear. This study examines the clinical features of ALS patients harboring the ANXA11 hotspot mutation p.P36R, characterized by late-onset motor neuron disease and occasional multi-system involvement.
View Article and Find Full Text PDFNat Commun
January 2025
CIRI, Centre International de Recherche en Infectiologie Univ Lyon, Inserm, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, ENS de Lyon, F-69007, Lyon, France.
Prime Editing can rewrite genes in living cells by allowing point mutations, deletions, or insertion of small DNA sequences with high precision. However, its safe and efficient delivery into human stem cells remains a technical challenge. In this report, we engineer Nanoscribes, virus-like particles that encapsidate ribonucleoprotein complexes of the Prime Editing system and allow their delivery into recipient cells.
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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