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骨髓增生异常综合征中检查点和 microRNA 处理基因的高突变负担。

High mutation burden in the checkpoint and micro-RNA processing genes in myelodysplastic syndrome.

机构信息

RM Gorbacheva Research Institute, Pavlov University, Saint-Petersburg, Russian Federation.

Bioinformatics Department, Pavlov University, Saint-Petersburg, Russian Federation.

出版信息

PLoS One. 2021 Mar 17;16(3):e0248430. doi: 10.1371/journal.pone.0248430. eCollection 2021.

DOI:10.1371/journal.pone.0248430
PMID:33730109
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7968630/
Abstract

A number of sequencing studies identified the prognostic impact of somatic mutations in myelodysplastic syndrome (MDS). However the majority of them focused on methylation regulation, apoptosis and proliferation genes. Despite the number of experimental studies published on the role of micro-RNA processing and checkpoint genes in the development of MDS, the clinical data about mutational landscape in these genes is limited. We performed a pilot study which evaluated mutational burden in these genes and their association with common MDS mutations. High prevalence of mutations was observed in the genes studied: 54% had mutations in DICER1, 46% had mutations in LAG3, 20% in CTLA4, 23% in B7-H3, 17% in DROSHA, 14% in PD-1 and 3% in PD-1L. Cluster analysis that included these mutations along with mutations in ASXL1, DNMT3A, EZH2, IDH1, RUNX1, SF3B1, SRSF2, TET2 and TP53 effectively predicted overall survival in the study group (HR 4.2, 95%CI 1.3-13.6, p = 0.016). The study results create the rational for incorporating micro-RNA processing and checkpoint genes in the sequencing panels for MDS and evaluate their role in the multicenter studies.

摘要

多项测序研究确定了骨髓增生异常综合征(MDS)体细胞突变的预后影响。然而,大多数研究都集中在甲基化调控、凋亡和增殖基因上。尽管已经有许多关于微 RNA 处理和检查点基因在 MDS 发生发展中的作用的实验研究发表,但这些基因的突变景观的临床数据是有限的。我们进行了一项试点研究,评估了这些基因中的突变负担及其与常见 MDS 突变的相关性。在所研究的基因中观察到突变的高发生率:54%的 DICER1 基因突变,46%的 LAG3 基因突变,20%的 CTLA4 基因突变,23%的 B7-H3 基因突变,17%的 DROSHA 基因突变,14%的 PD-1 基因突变和 3%的 PD-1L 基因突变。包括这些突变以及 ASXL1、DNMT3A、EZH2、IDH1、RUNX1、SF3B1、SRSF2、TET2 和 TP53 突变的聚类分析有效地预测了研究组的总生存率(HR 4.2,95%CI 1.3-13.6,p = 0.016)。研究结果为在 MDS 测序面板中纳入微 RNA 处理和检查点基因提供了依据,并评估了它们在多中心研究中的作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc33/7968630/c299271c1873/pone.0248430.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc33/7968630/74180bbe5152/pone.0248430.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc33/7968630/a78b9670ea09/pone.0248430.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc33/7968630/c299271c1873/pone.0248430.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc33/7968630/74180bbe5152/pone.0248430.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc33/7968630/a78b9670ea09/pone.0248430.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc33/7968630/c299271c1873/pone.0248430.g003.jpg

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