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A CpG Methylation Classifier to Predict Relapse in Adults with T-Cell Lymphoblastic Lymphoma.

Authors :
Tian XP
Su N
Wang L
Huang WJ
Liu YH
Zhang X
Huang HQ
Lin TY
Ma SY
Rao HL
Li M
Liu F
Zhang F
Zhong LY
Liang L
Lan XL
Li J
Liao B
Li ZH
Tang QL
Liang Q
Shao CK
Zhai QL
Cheng RF
Sun Q
Ru K
Gu X
Lin XN
Yi K
Shuang YR
Chen XD
Dong W
Sun C
Sang W
Liu H
Zhu ZG
Rao J
Guo QN
Zhou Y
Meng XL
Zhu Y
Hu CL
Jiang YR
Zhang Y
Gao HY
He WJ
Xia ZJ
Pan XY
Hai L
Li GW
Song LY
Kang TB
Xie D
Cai QQ
Source :
Clinical cancer research : an official journal of the American Association for Cancer Research [Clin Cancer Res] 2020 Jul 15; Vol. 26 (14), pp. 3760-3770. Date of Electronic Publication: 2020 Mar 31.
Publication Year :
2020

Abstract

Purpose: Adults with T-cell lymphoblastic lymphoma (T-LBL) generally benefit from treatment with acute lymphoblastic leukemia (ALL)-like regimens, but approximately 40% will relapse after such treatment. We evaluated the value of CpG methylation in predicting relapse for adults with T-LBL treated with ALL-like regimens.<br />Experimental Design: A total of 549 adults with T-LBL from 27 medical centers were included in the analysis. Using the Illumina Methylation 850K Beadchip, 44 relapse-related CpGs were identified from 49 T-LBL samples by two algorithms: least absolute shrinkage and selector operation (LASSO) and support vector machine-recursive feature elimination (SVM-RFE). We built a four-CpG classifier using LASSO Cox regression based on association between the methylation level of CpGs and relapse-free survival in the training cohort ( n = 160). The four-CpG classifier was validated in the internal testing cohort ( n = 68) and independent validation cohort ( n = 321).<br />Results: The four-CpG-based classifier discriminated patients with T-LBL at high risk of relapse in the training cohort from those at low risk ( P < 0.001). This classifier also showed good predictive value in the internal testing cohort ( P < 0.001) and the independent validation cohort ( P < 0.001). A nomogram incorporating five independent prognostic factors including the CpG-based classifier, lactate dehydrogenase levels, Eastern Cooperative Oncology Group performance status, central nervous system involvement, and NOTCH1 / FBXW7 status showed a significantly higher predictive accuracy than each single variable. Stratification into different subgroups by the nomogram helped identify the subset of patients who most benefited from more intensive chemotherapy and/or sequential hematopoietic stem cell transplantation.<br />Conclusions: Our four-CpG-based classifier could predict disease relapse in patients with T-LBL, and could be used to guide treatment decision.<br /> (©2020 American Association for Cancer Research.)

Details

Language :
English
ISSN :
1557-3265
Volume :
26
Issue :
14
Database :
MEDLINE
Journal :
Clinical cancer research : an official journal of the American Association for Cancer Research
Publication Type :
Academic Journal
Accession number :
32234760
Full Text :
https://doi.org/10.1158/1078-0432.CCR-19-4207