Evidence map›Paper›PMID 36256461›Full record

ArticleJCI insight2022

Molecular profiling identifies distinct subtypes across TP53 mutant tumors.

Xin Chen, Tianqi Liu, Jianqi Wu, Chen Zhu, Gefei Guan, Cunyi Zou, Qing Guo, Xiaolin Ren, Chen Li, Peng Cheng and 2 more

Open access · goldAbstract read
In one paragraph

Article in JCI insight, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.9field-weighted citation impact, top 23% 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

7 citing papers in PubMed, 9 citations in OpenAlex.

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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

12 authors at 2 institutions in 1 country.

Xin ChenDepartment of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.
Tianqi LiuDepartment of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.
Jianqi WuDepartment of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.
Chen ZhuDepartment of Neurosurgery, The First Hospital of China Medical University, Shenyang, Liaoning, China.
Gefei GuanDepartment of Neurosurgery, The First Hospital of China Medical University, Shenyang, Liaoning, China.
Cunyi ZouDepartment of Neurosurgery, The First Hospital of China Medical University, Shenyang, Liaoning, China.
Qing GuoDepartment of Neurosurgery, The First Hospital of China Medical University, Shenyang, Liaoning, China.
Xiaolin RenDepartment of Neurosurgery, The First Hospital of China Medical University, Shenyang, Liaoning, China.
Chen LiDepartment of Orthodontics, Stomatological Hospital of China Medical University, Shenyang, Liaoning, China.
Peng ChengDepartment of Neurosurgery, The First Hospital of China Medical University, Shenyang, Liaoning, China.
Wen ChengDepartment of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.
Anhua WuDepartment of Neurosurgery, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.
China Medical University · CNFirst Hospital of China Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tumor protein 53 mutation (TP53mut) is one of the most important driver events facilitating tumorigenesis, which could induce a series of chain reactions to promote tumor malignant transformation. However, the malignancy progression patterns under TP53 mutation remain less known. Clarifying the molecular landscapes of TP53mut tumors will help us understand the process of tumor development and aid precise treatment. Here, we distilled genetic and epigenetic features altered in TP53mut cancers for cluster-of-clusters analysis. Using integrated classification, we derived 5 different subtypes of TP53mut patients. These subtypes have distinct features in genomic alteration, clinical relevance, microenvironment dysregulation, and potential therapeutics. Among the 5 subtypes, COCA3 was identified as the subtype with worst prognosis, causing an immunosuppressive microenvironment and immunotherapeutic resistance. Further drug efficacy research highlighted olaparib as the most promising therapeutic agents for COCA3 tumors. Importantly, the therapeutic efficacy of olaparib in COCA3 and immunotherapy in non-COCA3 tumors was validated via in vivo experimentation. Our study explored the important molecular events and developed a subtype classification system with distinct targeted therapy strategies for different subtypes of TP53mut tumors. These multiomics classification systems provide a valuable resource that significantly expands the knowledge of TP53mut tumors and may eventually benefit in clinical practice.

Indexed as

GenomicsNeoplasmsEpigenomicsHumansTumor MicroenvironmentTumor Suppressor Protein p53TP53 protein, humanTumor Suppressor Protein p53GeneticsImmunologyImmunotherapyp53

Identifiers

PMID36256461
PMCPMC9746906
OpenAlexW4306708205

What OpenQuestion holds

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LicenceCC BY
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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.