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

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 ( = 160). The four-CpG classifier was validated in the internal testing cohort ( = 68) and independent validation cohort ( = 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 ( < 0.001). This classifier also showed good predictive value in the internal testing cohort ( < 0.001) and the independent validation cohort ( < 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 / 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.