Genomic hallmarks and therapeutic targets of ribosome biogenesis in cancer

Author:

Zang Yue1,Ran Xia2,Yuan Jie3,Wu Hao4,Wang Youya4,Li He4,Teng Huajing5,Sun Zhongsheng6ORCID

Affiliation:

1. HIM-BGI Omics Center, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences and Institute of Genomic Medicine, Wenzhou Medical University , China

2. Liangzhu Laboratory, Zhejiang University Medical Center , China

3. BGI Education Center, University of Chinese Academy of Sciences , China

4. Institute of Genomic Medicine, Wenzhou Medical University , China

5. Department of Radiation Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education) at Peking University Cancer Hospital and Institute , Beijing 100142, China

6. HIM-BGI Omics Center, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Institute of Genomic Medicine, Wenzhou Medical University, and Beijing Institutes of Life Science, Chinese Academy of Sciences , Hangzhou, China

Abstract

Abstract Hyperactive ribosome biogenesis (RiboSis) fuels unrestricted cell proliferation, whereas genomic hallmarks and therapeutic targets of RiboSis in cancers remain elusive, and efficient approaches to quantify RiboSis activity are still limited. Here, we have established an in silico approach to conveniently score RiboSis activity based on individual transcriptome data. By employing this novel approach and RNA-seq data of 14 645 samples from TCGA/GTEx dataset and 917 294 single-cell expression profiles across 13 cancer types, we observed the elevated activity of RiboSis in malignant cells of various human cancers, and high risk of severe outcomes in patients with high RiboSis activity. Our mining of pan-cancer multi-omics data characterized numerous molecular alterations of RiboSis, and unveiled the predominant somatic alteration in RiboSis genes was copy number variation. A total of 128 RiboSis genes, including EXOSC4, BOP1, RPLP0P6 and UTP23, were identified as potential therapeutic targets. Interestingly, we observed that the activity of RiboSis was associated with TP53 mutations, and hyperactive RiboSis was associated with poor outcomes in lung cancer patients without TP53 mutations, highlighting the importance of considering TP53 mutations during therapy by impairing RiboSis. Moreover, we predicted 23 compounds, including methotrexate and CX-5461, associated with the expression signature of RiboSis genes. The current study generates a comprehensive blueprint of molecular alterations in RiboSis genes across cancers, which provides a valuable resource for RiboSis-based anti-tumor therapy.

Funder

National Natural Science Foundation of China

Beijing Natural Science Foundation

Publisher

Oxford University Press (OUP)

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