Systematic screening for potential therapeutic targets in osteosarcoma through a kinome-wide CRISPR-Cas9 library

通过全激酶组 CRISPR-Cas9 文库系统筛选骨肉瘤的潜在治疗靶点

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作者:Yuanzhong Wu, Liwen Zhou, Zifeng Wang, Xin Wang, Ruhua Zhang, Lisi Zheng, Tiebang Kang

Conclusions

Our results not only offer potential therapeutic kinase targets in osteosarcoma but also provide a paradigm for functional genetic screening by using a CRISPR-Cas9 library, including target design, library construction, screening workflow, data analysis, and functional validation. This method may also be useful in potentially accelerating drug discovery for other cancer types.

Methods

We constructed a kinome-targeting CRISPR-Cas9 library containing 507 kinases and 100 nontargeting controls and screened the potential kinase targets in osteosarcoma. The CRISPR screening sequencing data were analyzed with the Model-based Analysis of Genome-wide CRISPR/Cas9 Knockout (MAGeCK) Python package. The functional data were applied in the 143B cell line through lenti-CRISPR-mediated gene knockout. The clinical significance of kinases in the survival of patients with osteosarcoma was analyzed in the R2: Genomics Analysis and Visualization Platform.

Objective

Osteosarcoma is the most common primary malignant bone tumor. However, the survival of patients with osteosarcoma has remained unchanged during the past 30 years, owing to a lack of efficient therapeutic targets.

Results

We identified 53 potential kinase targets in osteosarcoma. Among these targets, we analyzed 3 kinases, TRRAP, PKMYT1, and TP53RK, to validate their oncogenic functions in osteosarcoma. PKMYT1 and TP53RK showed higher expression in osteosarcoma than in normal bone tissue, whereas TRRAP showed no significant difference. High expression of all 3 kinases was associated with relatively poor prognosis in patients with osteosarcoma. Conclusions: Our results not only offer potential therapeutic kinase targets in osteosarcoma but also provide a paradigm for functional genetic screening by using a CRISPR-Cas9 library, including target design, library construction, screening workflow, data analysis, and functional validation. This method may also be useful in potentially accelerating drug discovery for other cancer types.

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