Evidence map›Paper›PMID 38343327›Full record

ArticleBriefings in bioinformatics2024

Genomic hallmarks and therapeutic targets of ribosome biogenesis in cancer.

Yue Zang, Xia Ran, Jie Yuan, Hao Wu, Youya Wang, He Li, Huajing Teng, Zhongsheng Sun

Open access · goldAbstract read
In one paragraph

Article in Briefings in bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed
11.0field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

45 citing papers in PubMed, 47 citations in OpenAlex.

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  9. Pancancer Analysis and the Oncogenic Role ofInternational journal of molecular sciences · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 5 institutions in 1 country.

Yue ZangHIM-BGI Omics Center, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences and Institute of Genomic Medicine, Wenzhou Medical University, China.
Xia RanLiangzhu Laboratory, Zhejiang University Medical Center, China.
Jie YuanBGI Education Center, University of Chinese Academy of Sciences, China.
Hao WuInstitute of Genomic Medicine, Wenzhou Medical University, China.
Youya WangInstitute of Genomic Medicine, Wenzhou Medical University, China.
He LiInstitute of Genomic Medicine, Wenzhou Medical University, China.
Huajing TengDepartment of Radiation Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education) at Peking University Cancer Hospital and Institute, Beijing 100142, China.
Zhongsheng SunHIM-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.ORCID 0000-0003-1992-2681
Wenzhou Medical University · CNChinese Academy of Sciences · CNPeking University · CNUniversity of Chinese Academy of Sciences · CNZhejiang University · CN

Funding

Beijing Natural Science Foundation Z230007National Natural Science Foundation of China 32370684
6 · The paper itself

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.

Indexed as

DNA Copy Number VariationsNeoplasmsGenomicsHumansMutationRibosomesRNA-Binding ProteinsBOP1 protein, humanRNA-Binding Proteinsdrug responseimpaired ribosome biogenesis checkpointpan-cancer multi-omicsribosome biogenesistherapeutic target

Identifiers

PMID38343327
PMCPMC10859687
OpenAlexW4391758618

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.