A quick and reliable image-based AI algorithm for evaluating cellular senescence of gastric organoids

Objective:Organoids are a powerful tool with broad application prospects in biomedicine.Notably,they provide alternatives to animal models for testing potential drugs before clinical trials.However,the number of passages for which organoids maintain cellular vitality ex vivo remains unclear.Methods:Herein,we constructed 55 gastric organoids from 35 individuals,serially passaged the organoids,and captured microscopic images for phenotypic evaluation.Senescence-associatedβ-galactosidase(SA-β-Gal),cell diameter in suspension,and gene expression reflecting cell cycle regulation were examined.The YOLOv3 object detection algorithm integrated with a convolutional block attention module(CBAM)was used to evaluate organoid vitality.Results:SA-β-Gal staining intensity;single-cell diameter;and expression of p15,p16,p21,CCNA2,CCNE2,and LMNB1 reflected the progression of aging in organoids during passaging.The CBAM-YOLOv3 algorithm precisely evaluated aging organoids on the basis of organoid average diameter,organoid number,and number×diameter,and the findings positively correlated with SA-β-Gal staining and single-cell diameter.Organoids derived from normal gastric mucosa had limited passaging ability(passages 1–5),before aging,whereas tumor organoids showed unlimited passaging potential for more than 45 passages(511 days)without showing clear senescence.Conclusions:Given the lack of indicators for evaluating organoid growth status,we established a reliable approach for integrated analysis of phenotypic parameters that uses an artificial intelligence algorithm to indicate organoid vitality.This method enables precise evaluation of organoid status in biomedical studies and monitoring of living biobanks.

Benchmark for establishment of organoids from gastrointestinal epithelium and cancer based on available consumables and reagents

Gastrointestinal cancers are a public health problem that threatens the lives of human being. A good experimental model is a powerful tool to promote the uncovering pathogenesis and establish novel treatment methods. High-quality biomedical research requires experimental models to recapitulate the physiological and pathological states of their parental tissues as much as possible. Organoids are such experimental models. Organoids refer to small organlike cellular clusters formed by the expansion and passaging of living tissues in 3D culture medium in vitro.Organoids are highly similar to the original tissues in terms of cellular composition, cell functions, and genomic profiling. Organoids have many advantages, such as short preparation cycles, long-term storage based on cryopreservation, and reusability. In recent years, researchers carried out the establishment of organoids from gastrointestinal mucosa and cancer tissues, and accumulated valuable experiences. In order to promote effective usage and further development of organoid-related technologies in the research of gastrointestinal diseases, this study proposes a benchmark based on utilization of available experimental consumables and reagents, which are involved in the key steps such as collection and pretreatment of biospecimen, organoid construction, organoid cryopreservation and recovery, growth status evaluation, and organoid quality control. We believe that the standard for the construction and preservation of organoids derived from human gastrointestinal epithelium and cancer tissues can provide an important reference for the majority of scientific researchers.