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使用大规模基因组文库进行表型筛选以鉴定癌症治疗的药物靶点。

Phenotypic screening using large-scale genomic libraries to identify drug targets for the treatment of cancer.

作者信息

Sato Mitsuo

机构信息

Department of Pathophysiological Laboratory Sciences, Nagoya University Graduate School of Medicine, Nagoya, Aichi 461-8673, Japan.

出版信息

Oncol Lett. 2020 Jun;19(6):3617-3626. doi: 10.3892/ol.2020.11512. Epub 2020 Apr 3.

Abstract

During malignant progression to overt cancer cells, normal cells accumulate multiple genetic and non-genetic changes, which result in the acquisition of various oncogenic properties, such as uncontrolled proliferation, drug resistance, invasiveness, anoikis-resistance, the ability to bypass oncogene-induced senescence and cancer stemness. To identify potential novel drug targets contributing to these malignant phenotypes, researchers have performed large-scale genomic screening using various and screening models and identified numerous promising cancer drug target genes. However, there are issues with these identified genes, such as low reproducibility between different datasets. In the present study, the recent advances in the functional screening for identification of cancer drug target genes are summarized, and current issues and future perspectives are discussed.

摘要

在向明显癌细胞的恶性进展过程中,正常细胞积累了多种遗传和非遗传变化,这些变化导致获得各种致癌特性,如不受控制的增殖、耐药性、侵袭性、失巢凋亡抗性、绕过癌基因诱导的衰老的能力和癌症干性。为了确定促成这些恶性表型的潜在新型药物靶点,研究人员使用各种筛选模型进行了大规模基因组筛选,并确定了许多有前景的癌症药物靶基因。然而,这些已确定的基因存在一些问题,比如不同数据集之间的可重复性较低。在本研究中,总结了用于鉴定癌症药物靶基因的功能筛选的最新进展,并讨论了当前问题和未来前景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6ef/7204489/2abf54b332de/ol-19-06-3617-g00.jpg

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