Subgrouping by gene expression profiles to improve relapse risk prediction in paediatric B‐precursor acute lymphoblastic leukaemia

Abstract

Relapsed acute lymphoblastic leukaemia (ALL) remains a prevalent paediatric cancer and one of the most common causes of mortality from malignancy in children. Tailoring the intensity of therapy according to early stratification is a promising strategy but remains a major challenge due to heterogeneity and subtyping difficulty. In this study, we subgroup B‐precursor ALL patients by gene expression profiles, using non‐negative matrix factorization and minimum description length which unsupervisedly determines the number of subgroups. Within each of the four subgroups, logistic and Cox regression with elastic net regularization are used to build models predicting minimal residual disease (MRD) and relapse‐free survival (RFS) respectively. Measured by area under the receiver operating characteristic curve (AUC), subgrouping improves prediction of MRD in one subgroup which mostly overlaps with subtype TCF3‐PBX1 (AUC = 0·986 in the training set and 1·0 in the test set), compared to a global model published previously. The models predicting RFS displayed acceptable concordance in training set and discriminate high‐relapse‐risk patients in three subgroups of the test set (Wilcoxon test p = 0·048, 0·036, and 0·016). Genes playing roles in the models are specific to different subgroups. The improvement of subgrouped MRD prediction and the differences of genes in prediction models of subgroups suggest that the heterogeneity of B‐precursor ALL can be handled by subgrouping according to gene expression profiles to improve the prediction accuracy.

Transfer of miR‐4755‐5p through extracellular vesicles and particles induces decitabine resistance in recipient cells by targeting CDKN2B

“…Based on TCGA database, we found that miR‐4755‐5p was not only negatively correlated with CDKN2B, but also other potential target genes (Supporting Information: Figure ), such as WWC3 (WWC family member 3) and DNAJB5 (DnaJ heat shock family member B5). Both of them are tumor suppressor genes, 32–34 suggesting that miR‐4755‐5p may act as an oncogene in tumorigenesis. Validation study indicate that miR‐4755‐5p was upregulated in AML patients who are nonresponsive to DAC.…”

“…31 Based on TCGA database, we found that miR-4755-5p was not only negatively correlated with CDKN2B, but also other potential target genes (Supporting Information: Figure S1), such as WWC3 (WWC family member 3) and DNAJB5 (DnaJ heat shock family member B5). Both of them are tumor suppressor genes, [32][33][34] CDKN2B, an inhibitor of cyclin-dependent kinases, forms a complex with CDK4 or CDK6, and negatively regulated the G1/S progression within the cell cycle. 35 Unlike in solid tumors, CDKN2B is frequently hypermethylated 36 and contributes to the malignant progression of AML.…”