Literature DB >> 33391264

A TP53-Associated Immune Prognostic Signature for the Prediction of Overall Survival and Therapeutic Responses in Muscle-Invasive Bladder Cancer.

Xiangkun Wu1,2, Daojun Lv1,2, Chao Cai1,2, Zhijian Zhao1,2, Ming Wang1,2, Wenzhe Chen1,2, Yongda Liu1,2.   

Abstract

Background: TP53 gene mutation is one of the most common mutations in human bladder cancer (BC) and has been implicated in the progression and prognosis of BC.
Methods: RNA sequencing data and TP53 mutation data in different populations and platforms were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database to determine and validate a TP53-associated immune prognostic signature (TIPS) based on differentially expressed immune-related genes (DEIGs) between muscle-invasive bladder cancer (MIBC) patients with and without TP53 mutations.
Results: A total of 99 DEIGs were identified based on TP53 mutation status. TIPS including ORM1, PTHLH, and CTSE were developed and validated to identify high-risk prognostic group who had a poorer prognosis than low-risk prognostic group in TCGA and GEO database. The high-risk prognostic group were characterized by a higher abundance of regulatory T cells, myeloid-derived suppressor cells, and tumor-associated macrophages than the low-risk prognostic group. Moreover, they exhibited a lower abundance of CD56bright NK cells, higher expression of CTLA4, LAG3, PDCD1, TIGIT, and HAVCR2, as well as being more likely to respond to anti-PD-1, and neoadjuvant chemotherapy than the low-risk prognostic group. Based on TIPS and other clinical characteristics, a nomogram was constructed for clinical use.
Conclusion: TIPS derived from TP53 mutation status is a potential prognostic signature or therapeutic target but additional prospective studies are necessary to confirm this potential.
Copyright © 2020 Wu, Lv, Cai, Zhao, Wang, Chen and Liu.

Entities:  

Keywords:  TP53 mutation; immune prognostic signature; muscle-invasive bladder cancer; nomogram; the cancer genome atlas (TCGA) and gene expression omnibus (GEO) database

Mesh:

Substances:

Year:  2020        PMID: 33391264      PMCID: PMC7774015          DOI: 10.3389/fimmu.2020.590618

Source DB:  PubMed          Journal:  Front Immunol        ISSN: 1664-3224            Impact factor:   7.561


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