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    Home > Biochemistry News > Biotechnology News > Grouped-seq: a high-throughput analysis platform technology that can simultaneously obtain tumor organoid phenotype and expression profile information

    Grouped-seq: a high-throughput analysis platform technology that can simultaneously obtain tumor organoid phenotype and expression profile information

    • Last Update: 2021-12-28
    • Source: Internet
    • Author: User
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    On December 10, 2021, the research group of Researcher Liu Peng from the Department of Biomedical Engineering of Tsinghua University School of Medicine and Associate Professor Chen Xiaofang of Beijing Aviation University published an online publication titled Grouped-seq for integrated phenotypic and transcriptomic screening of patient in the academic journal Nucleic Acids Research -A research paper on derived tumor organoids , reporting a new technology that can simultaneously obtain phenotype and corresponding expression profile changes from micro tumor organoids at high throughput and low cost .


    In recent years, tumor organoids (Patient-derived organoids, PDOs) have developed into a powerful in vitro model for studying patient drug response and its internal mechanism of action


    In order to solve the above two major problems, Liu Peng's research group has successfully developed a Grouped-seq (genome-wide RNA output unified with phenotypic data sequencing) platform through six years of hard work, which provides diversified tools for PDOs drug screening


    The operating process of the Grouped-seq platform is shown in Figure 1


    Figure 1.


    In this study, colorectal cancer organoids were used to validate the Grouped-seq platform (Figure 2)


    Figure 2.


    Furthermore, this study conducted a more in-depth exploration of the medication mechanism of the drug irinotecan (Figure 3)


    Figure 3.


    Compared with traditional analysis techniques, Grouped-seq has the following three main improvements


    Tsinghua University School of Medicine doctoral student Wu Maoshuai is the first author of the paper.


    Original link: https://academic.



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