Low levels of wilms tumor 1 (WT1) protein are prognostically adverse and independent of mutation status in acute myelogenous leukemia

Abstract INTRODUCTION: Mutations in the Wilms Tumor 1 (WT1) occur in 6-15% of Acute Myelogenous Leukemia (AML) cases, and is associated with poor prognosis. These recurrent somatic mutations usually lead to loss of enzymatic function, causing a genome-wide reduction in 5-hydroxymethylcytosine (5-hmc), ultimately leading to DNA hypermethylation. Notably, overexpression of WT1 mRNA occurs in 90% of AML cases, also conferring adverse prognosis. Moreover, WT1 mutations (MUT) that cause low protein expression are associated with chemoresistance in AML. We hypothesized that low levels of the wild-type (WdT) WT1 protein would produce a similarly bad prognosis. METHODS: We measured the levels of 434 proteins using Reverse Phase Protein Arrays in 806 newly diagnosed, fresh, pre-treatment and 95% blast enriched AML samples. Protein expression was normalized to non-G-CSF treated, normal bone marrow-derived CD34+ cells. WT1 mutation status, treatment, and outcome data were known for 482 patients: 29 (~6%) with WT1 mutation (MUT), 423 were WdT. LogRank tests were used to compared outcomes; Fisher's Exact, Pearson's Chi-squared or Wilcoxon tests for comparing variables; Pearson's correlation for protein correlation (p0.01 and R0.2); Wilcoxon tests adjusted by FDR for differential expression (p0.05 and LFC0.5); and Cox proportional hazards models (CoxPH) for Uni-(UV) and Multi-variate (MV) analysis. RESULTS: The cohort was divided into quintiles and regrouped into upper 1/5th, named High (WT N=81, MUT N=7) and lower 4/5th, termed Low (WT N=342, MUT N=22). Low WT1 WdT cases had lower WBC count and blood blasts percentage, and a higher frequency of 2nd AML, unfavorable cytogenetics, -7/7q- and mutations in ASLX1, MLL, RUNX1 and TP53 (P 0.001, 0.001, 0.002, 0.016, 0.03, 0.001, 0.04, 0.006, 0.03). High WT1 WdT patients had better prognosis compared to Low expressing ones (5yrs OS: WdT-Low=21%, WdT-High=38%; p0.05). Notably, High WdT cases responded well to AraC-based intensive chemotherapy (IC), but did poorly with Venetoclax plus Hypomethylating agent (VH), whereas Low WdT patients treated with either therapy performed worse than High WdT treated with IC, but better than the cases that received VH (5ys OS: IC WdT-Low=32%, IC WdT-High=56%, VH WdT-Low=17%, VH WdT-High=0%; P=0.0003). A similar pattern was observed for Remission Duration (RD), with WT1 WdT High patients performing better with IC compared to VH and Low ones doing worse independent of therapy (5ys RD: IC WdT-High=76%, IC WdT-Low=56%, VH WdT-High=0%, VH WdT-Low=36%; P=0.006). For the CoxPH models of OS, we separated WdT WT1 patients by expression levels and therapy, resulting in 4 prognostic groups: IC High, IC Low, VH High and VH Low. In the UV analysis, all 4 groups were prognostic, along with other clinical, cytogenetic and molecular features (e.g. age, unfavorable cytogenetics, 2nd AML, mutations in ASLX1, FLT3-ITD, JAK2, CEBPA, etc.). In the MV model, only IC High and VH High retained significance, as well as age, 2nd AML and CEBPA MUT. We also compared the protein signature of WT1 WdT-Low patients with WT1-MUT to search for differences and commonalities between them. The differential expression (DE) analysis, yielded 4 proteins (BCL11A, NLN, SSBP2, and TP53BP1), all down-regulated in WdT-Low. Protein-protein correlations between WT1 and the other 433 in our database showed little overlap, with only 3 significantly correlated proteins in both WdT-Low and MUT WT1 (BCL11A, FOXM1 and HIST3H3). Moreover, DE analysis between WdT-Low and WdT-High revealed 49 proteins (23 up- and 26 down-regulated in WdT-Low), which are mostly connected to VEGF signaling, focal adhesion and negative regulation of apoptosis. CONCLUSIONS: Patients with WT1 WdT-Low expression had a worse prognosis compared to WT1 WdT-High patients. WT1 WdT-High cases performed better, when treated with IC and not VH, suggesting that correct therapy recommendation is crucial for these patients. The proteomic signature of WT1 WdT-Low was dissimilar to WT1 MUT, suggesting a different pathophysiology. DE between WdT-Low vs High revealed potential therapeutic signaling cascades, such as VEGF pathway, which could be targeted to improve outcomes. Finally, proteomics could be used to prospectively triage patients based on WT1 levels to identify the WdT cases that could benefit from WT1-directed therapy.