| Autor: |
Xin Chen, Tianqi Liu, Jianqi Wu, Chen Zhu, Gefei Guan, Cunyi Zou, Qing Guo, Xiaolin Ren, Chen Li, Peng Cheng, Wen Cheng, Anhua Wu |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
JCI Insight, Vol 7, Iss 23 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2379-3708 |
| DOI: |
10.1172/jci.insight.156485 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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