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一种用于预测弥漫性大B细胞淋巴瘤患者预后的新型定义的超级增强子相关基因特征。

A Novel Defined Super-Enhancer Associated Gene Signature to Predict Prognosis in Patients With Diffuse Large B-Cell Lymphoma.

作者信息

Xu Hong, Li Yuhang, Jiang Yanan, Wang Jinhuan, Sun Huimeng, Wu Wenqi, Lv Yangyang, Liu Su, Zhai Yixin, Tian LinYan, Li Lanfang, Zhao Zhigang

机构信息

Department of Hematology, Key Laboratory of Cancer Prevention and Therapy, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.

Department of Oncology, Institute of Urology, Second Hospital of Tianjin Medical University, Tianjin, China.

出版信息

Front Genet. 2022 Jun 14;13:827840. doi: 10.3389/fgene.2022.827840. eCollection 2022.

DOI:10.3389/fgene.2022.827840
PMID:35774514
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9237400/
Abstract

Diffuse large B-cell lymphoma (DLBCL) is a genetically heterogeneous disease that can have profound differences in survival outcomes. A variety of powerful prognostic factors and models have been constructed; however, the development of more accurate prognosis prediction and targeted treatment for DLBCL still faces challenges. An explosion of research on super-enhancer (SE)-associated genes provide the possibility to use in prognostication for cancer patients. Here, we aimed to establish a novel effective prognostic model using SE-associated genes from DLBCL. A total of 1,105 DLBCL patients from the Gene Expression Omnibus database were included in this study and were divided into a training set and a validation set. A total of 11 SE-associated genes (BCL2, SPAG16, PXK, BTG1, LRRC37A2, EXT1, TGFBR2, ANKRD12, MYCBP2, PAX5, and MYC) were initially screened and identified by the least absolute shrinkage and selection operator (Lasso) penalized Cox regression, univariate and multivariate Cox regression analysis. Finally, a risk score model based on these 11 genes was constructed. Kaplan-Meier (K-M) curves showed that the low-risk group appeared to have better clinical survival outcomes. The excellent performance of the model was determined time-dependent receiver operating characteristic (ROC) curves. A nomogram based on the polygenic risk score was further established to promote reliable prognostic prediction. This study proposed that the SE-associated-gene risk signature can effectively predict the response to chemotherapy in DLBCL patients. A novel and reliable SE-associated-gene signature that can effectively classify DLBCL patients into high-risk and low-risk groups in terms of overall survival was developed, which may assist clinicians in the treatment of DLBCL.

摘要

弥漫性大B细胞淋巴瘤(DLBCL)是一种基因异质性疾病,其生存结果可能存在显著差异。目前已经构建了多种强大的预后因素和模型;然而,为DLBCL开发更准确的预后预测和靶向治疗仍然面临挑战。对超级增强子(SE)相关基因的大量研究为癌症患者的预后评估提供了可能。在此,我们旨在利用DLBCL的SE相关基因建立一种新型有效的预后模型。本研究纳入了基因表达综合数据库中的1105例DLBCL患者,并将其分为训练集和验证集。通过最小绝对收缩和选择算子(Lasso)惩罚Cox回归、单变量和多变量Cox回归分析,初步筛选并鉴定出11个SE相关基因(BCL2、SPAG16、PXK、BTG1、LRRC37A2、EXT1、TGFBR2、ANKRD12、MYCBP2、PAX5和MYC)。最后,基于这11个基因构建了风险评分模型。Kaplan-Meier(K-M)曲线显示,低风险组似乎具有更好的临床生存结果。通过时间依赖受试者工作特征(ROC)曲线确定了该模型的优异性能。进一步建立了基于多基因风险评分的列线图,以促进可靠的预后预测。本研究表明,SE相关基因风险特征可以有效预测DLBCL患者对化疗的反应。开发了一种新型且可靠的SE相关基因特征,可根据总生存期将DLBCL患者有效分为高风险和低风险组,这可能有助于临床医生治疗DLBCL。

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