Novel WT1 Target Genes: IL-2, IL-2RB, and IL-2RG Discovered during WT1 Silencing Using Lentiviral-Based RNAi in Myeloid Leukemia Cells

Shikonin as a WT1 Inhibitor Promotes Promyeloid Leukemia Cell Differentiation

This study aims to observe the differentiating effect of shikonin on Wilms' tumor 1 (WT1)-positive HL-60 cells and investigate the fate of the differentiated leukemia cells. WT1 overexpression unaffected cell viability but promoted resistance to H₂O₂-induced DNA injury and cell apoptosis. The binding of shikonin to the WT1 protein was confirmed by molecular docking and drug affinity reaction target stability (DARTS). Shikonin at the non-cytotoxic concentration could decrease the WT1 protein and simultaneously reduced the CD34 protein and increased the CD11b protein in a dose-dependent manner in normal HL-60 cells but not in WT1-overexpressed HL-60 cells. Shikonin unaffected HL-60 cell viability in 48 h. However, it lasted for 10 days; could attenuate cell proliferation, mitochondrial membrane potential (MMP), and self-renewal; prevent the cell cycle; promote cell apoptosis. In a mouse leukemia model, shikonin could decrease the WT1 protein to prevent leukemia development in a dose-dependent manner. In this study, we also confirmed preliminarily the protein-protein interactions between WT1 and CD34 in molecular docking and CO-IP assay. Our results suggest that: 1. shikonin can down-regulate the WT1 protein level for leukemia differentiation therapy, and 2. the interaction between WT1 and CD34 proteins may be responsible for granulocyte/monocyte immaturity in HL-60 cells.

Deregulated transcription factors and poor clinical outcomes in cancer patients

Transcription factors are a group of proteins, which possess DNA-binding domains, bind to DNA strands of promoters or enhancers, and initiate transcription of genes with cooperation of RNA polymerase and other co-factors. They play crucial roles in regulating transcription during embryogenesis and development. Their physiological status in different cell types is also important to maintain cellular homeostasis. Therefore, any deregulation of transcription factors will lead to the development of cancer cells and tumor progression. Based on their functions in cancer cells, transcription factors could be either oncogenic or tumor suppressive. Furthermore, transcription factors have been shown to modulate cancer stem cells, epithelial-mesenchymal transition (EMT) and drug response; therefore, measuring deregulated transcription factors is hypothesized to predict treatment outcomes of patients with cancers and targeting deregulated transcription factors could be an encouraging strategy for cancer therapy. Here, we summarize the current knowledge of major deregulated transcription factors and their effects on causing poor clinical outcome of patients with cancer. The information presented here will help to predict the prognosis and drug response and to design novel drugs and therapeutic strategies for the treatment of cancers by targeting deregulated transcription factors.

Depth of Response to Intensive Chemotherapy Has Significant Prognostic Value among Acute Myeloid Leukemia (AML) Patients Undergoing Allogeneic Hematopoietic Stem-Cell Transplantation with Intermediate or Adverse Risk at Diagnosis Compared to At-Risk Group According to European Leukemia Net 2017 Risk Stratification

We evaluated the prognostic efficiency of the European Leukemia Net (ELN) 2017 criteria on the post-transplant outcomes of 174 patients with intermediate (INT; n = 108, 62%) or adverse (ADV) risk (n = 66, 38%) of acute myeloid leukemia; these patients had received the first allogeneic hematopoietic stem-cell transplantation (HSCT) at remission. After a median follow-up period of 18 months, the 2 year OS, RFS, and CIR after HSCT were estimated to be 58.6% vs. 64.4% (p = 0.299), 50.5% vs. 53.7% (p = 0.533), and 26.9% vs. 36.9% (p = 0.060) in the INT and ADV risk groups, respectively. Compared to the ELN 2017 stratification, pre-HSCT WT1 levels (cutoff: 250 copies/104 ABL) more effectively segregated the post-HSCT outcomes of INT risk patients compared to ADV risk patients regarding their 2 year OS (64.2% vs. 51.5%, p = 0.099), RFS (59.4% vs. 32.4%, p = 0.003), and CIR (18.9% vs. 60.0% p < 0.001). Indeed, high WT1 levels were more prominent in INT risk patients than in ADV risk patients. Notably, FLT3-ITD had the greatest impact on post-HSCT outcomes among all the ELN 2017 criteria components; patients in the FLT3-ITD mutant subgroups exhibited the worst outcomes regardless of their allelic ratios or NPM1 status compared to the pre-HSCT WT1 level of other INT and ADV risk patients.