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确定真正的高危 TP53 突变弥漫性大 B 细胞淋巴瘤患者,并探索潜在的生物学机制。

Identify truly high-risk TP53-mutated diffuse large B cell lymphoma patients and explore the underlying biological mechanisms.

机构信息

Department of Hematology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, 210029, China.

Key Laboratory of Hematology, Nanjing Medical University, Nanjing, 210029, China.

出版信息

Cell Commun Signal. 2024 Aug 15;22(1):401. doi: 10.1186/s12964-024-01765-w.

DOI:10.1186/s12964-024-01765-w
PMID:39148095
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11325619/
Abstract

TP53 mutation (TP53-mut) correlates with inferior survival in many cancers, whereas its prognostic role in diffuse large B-cell lymphoma (DLBCL) is still in controversy. Therefore, more precise risk stratification needs to be further explored for TP53-mut DLBCL patients. A set of 2637 DLBCL cases from multiple cohorts, was enrolled in our analysis. Among the 2637 DLBCL patients, 14.0% patients (370/2637) had TP53-mut. Since missense mutations account for the vast majority of TP53-mut DLBCL patients, and most non-missense mutations affect the function of the P53 protein, leading to worse survival rates, we distinguished patients with missense mutations. A TP53 missense mutation risk model was constructed based on a 150-combination machine learning computational framework, demonstrating excellent performance in predicting prognosis. Further analysis revealed that patients with high-risk missense mutations are significantly associated with early progression and exhibit dysregulation of multiple immune and metabolic pathways at the transcriptional level. Additionally, the high-risk group showed an absolutely suppressed immune microenvironment. To stratify the entire cohort of TP53-mut DLBCL, we combined clinical characteristics and ultimately constructed the TP53 Prognostic Index (TP53PI) model. In summary, we identified the truly high-risk TP53-mut DLBCL patients and explained this difference at the mutation and transcriptional levels.

摘要

TP53 突变(TP53-mut)与许多癌症的不良预后相关,而其在弥漫性大 B 细胞淋巴瘤(DLBCL)中的预后作用仍存在争议。因此,需要进一步探索更精确的风险分层来评估 TP53-mut DLBCL 患者。我们对来自多个队列的 2637 例 DLBCL 病例进行了分析。在这 2637 例 DLBCL 患者中,有 14.0%(370/2637)的患者存在 TP53-mut。由于错义突变占 TP53-mut DLBCL 患者的绝大多数,并且大多数非错义突变会影响 P53 蛋白的功能,导致生存率更差,因此我们将患者分为存在错义突变和不存在错义突变。基于一个包含 150 个组合的机器学习计算框架构建了 TP53 错义突变风险模型,该模型在预测预后方面表现出优异的性能。进一步分析显示,高风险错义突变患者与早期进展显著相关,并在转录水平上表现出多个免疫和代谢途径的失调。此外,高风险组显示出绝对抑制的免疫微环境。为了对整个 TP53-mut DLBCL 队列进行分层,我们结合了临床特征,并最终构建了 TP53 预后指数(TP53PI)模型。总之,我们确定了真正的高风险 TP53-mut DLBCL 患者,并在突变和转录水平上解释了这种差异。

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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9377/11325619/f06145e3f048/12964_2024_1765_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9377/11325619/f70f25ba9651/12964_2024_1765_Fig2_HTML.jpg
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