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

التفاصيل البيبلوغرافية
العنوان: Data from A CpG Methylation Classifier to Predict Relapse in Adults with T-Cell Lymphoblastic Lymphoma
المؤلفون: Qing-Qing Cai, Dan Xie, Tie-Bang Kang, Li-Yan Song, Guo-Wei Li, Lan Hai, Xue-Yi Pan, Zhong-Jun Xia, Wen-Jun He, Hong-Yi Gao, Ying Zhang, Yi-Rong Jiang, Chang-Lu Hu, Yong Zhu, Xiang-Ling Meng, Ying Zhou, Qiao-Nan Guo, Jun Rao, Zhi-Gang Zhu, Hui Liu, Wei Sang, Cai Sun, Wei Dong, Xiao-Dong Chen, Yue-Rong Shuang, Kun Yi, Xi-Na Lin, Xia Gu, Kun Ru, Qi Sun, Run-Fen Cheng, Qiong-Li Zhai, Chun-Kui Shao, Qiong Liang, Qiong-Lan Tang, Zhi-Hua Li, Bing Liao, Juan Li, Xiao-Liang Lan, Li Liang, Li-Ye Zhong, Fen Zhang, Fang Liu, Mei Li, Hui-Lan Rao, Shu-Yun Ma, Tong-Yu Lin, Hui-Qiang Huang, Xi Zhang, Yan-Hui Liu, Wei-Juan Huang, Liang Wang, Ning Su, Xiao-Peng Tian
بيانات النشر: American Association for Cancer Research (AACR), 2023.
سنة النشر: 2023
الوصف: 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.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).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.Conclusions:Our four-CpG–based classifier could predict disease relapse in patients with T-LBL, and could be used to guide treatment decision.
DOI: 10.1158/1078-0432.c.6528984
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9b213781f5ba30c7bc4c3c8d14265f3b
https://doi.org/10.1158/1078-0432.c.6528984
Rights: OPEN
رقم الانضمام: edsair.doi.dedup.....9b213781f5ba30c7bc4c3c8d14265f3b
قاعدة البيانات: OpenAIRE
الوصف
DOI:10.1158/1078-0432.c.6528984