Vanin 1 (<i>VNN1</i>) levels predict poor outcome in acute myeloid leukemia
Authors: Valerio Izzi, Juho Lakkala, Raman Devarajan, Eeva‐Riitta Savolainen, Pirjo Koistinen, Ritva Heljasvaara, Taina Pihlajaniemi
Journal: American Journal of Hematology (2017)

Although up to 80% of acute myeloid leukemia (AML) patients can expect to enter a first complete remission period (CR1) after appropriate induction regimen,1 many will experience relapse depending on the success of following treatments and face a dismal prognosis.2 Identification of the factors underlying relapse and progression remain thus imperative to increase patients' chance to survive AML. To this aim, we have devised a robust transcriptomic analysis to identify genes upregulated in relapsed patients and drug-resistant AML cell lines and linearly associated with patient survival in multivariable analysis. We have found that (1) the expression of Vanin 1 (VNN1), an anti-apoptotic enzyme inhibiting caspases and scavenging reactive oxygen species,3 is significantly associated with relapse-, event-, or disease-free survival (RFS, EFS, and DFS, respectively) in multivariable models through different cohorts, (2) VNN1 levels ssociate with poor outcomes (resistance and relapse) at different stages of chemotherapy in a retrospective cohort assembled at the Oulu University Hospital, and (3) HOXB5 and IL2RA (CD25) are potentially involved in VNN1 regulation. These data suggest further investigation into VNN1 as a biomarker for relapse risk and for post-therapy assessment of patient status. All methods are reported in Supporting Information. As a starting point, we have investigated differential gene expression in patients with or without relapse/progression at two years after conventional cytarabine (ara-C) + tetracycline treatment in The Cancer Genome Atlas AML cohort (TCGA LAML) and compared it to differential gene expression in AML cell lines resistant to the same drugs vs. drug-sensitive lines (Supporting Information Figure S1). The resulting 6 differentially-regulated genes (DRGs, SPINK2, TM4SF1, VNN1, SYTL4, BEX1, TEAD4) were then inputted into a Cox proportional hazards (Cox-PH) model of patients' disease-free survival (DFS) that also included age, gender, karyotypical abnormalities, French-American-British (FAB) subgroups and major driver mutations (Supporting Information Table S1). VNN1, which had the largest hazard rate and Wald statistics and the lowest P value, was further studied. To facilitate cross-validation, VNN1 expression was dichotomized along the average (high: above the average, low: below the average) and tested in simpler Cox-PH models including the same variables in TCGA LAML, GSE10358, and TARGET-AML (Supporting Information Table S2). High VNN1 expression associated with significantly shorter DFS in TCGA LAML and shorter event-free survival (EFS) in GSE10358 and TARGET-AML (Figure 1A). Moreover, we found significantly shorter relapse-free survival (RFS) in the VNN1-high group of a retrospective AML cohort assembled at the Oulu University Hospital (Figure 1A and Supporting Information Table S3). Conformingly, cross-comparison of Cox-PH models of DFS or EFS (depending on the cohort) based on patients' age, gender and available driver genes or VNN1 shows that VNN1 expression yields concordance (C) values comparable to that of models based on the mutational status of FLT3, slightly lower than that based on NPM1, and significantly higher than the ones based on all other major driver mutations in AML (Supporting Information Figure S2). High VNN1 expression characterizes AML patients with a high risk of adverse outcome. (A) Multivariable endpoint survival analysis (Cox proportional hazards, Cox-PH) in four different AML cohorts. The effect of VNN1 expression (high: above cohort average, low: below cohort average) is reported. DFS: disease-free survival, EFS: event-free survival, RFS: relapse-free survival. HR: hazard rate, 95% CI: 95% confidence interval. (B) High expression of VNN1 at diagnosis identifies patients with a worse outcome after the first and second induction and the second and third consolidation (or last available follow-up), and (C) patients with higher mortality at 60 days after the first induction. CR: complete remission, MRD: minimal residual disease, Ref/Rel: refractory disease and/or relapse. (D) Response rate (% of patients in CR) in patients with high VNN1 expression is reduced at the passage from the first induction cycle (Ind1) to the first consolidation (Ind3/Con1) in respect to patients with low VNN1 expression, and is more significantly compromised at later stages (Con3/Last) We further evaluated the association of VNN1 expression with risk markers and therapy outcome in the Oulu retrospective cohort, for which we had access to complete clinical records. Overall, 60% of patients with high VNN1 expression experienced relapse in respect to 33% of patients with low VNN1 expression, and the only patients who relapsed after allogeneic hematopoietic stem cell transplantation (HSCT) were in the VNN1-high group (Supporting Information Figure S3A,B). Furthermore, expression of VNN1 was significantly higher in patients who needed two or more induction cycles with cytarabine to achieve remission in respect to those who achieved remission after the first induction, and was also linearly associated with increasing cytogenetic risk, though there was no interdependence between these two factors (P:0.955, Fisher's Exact) (Supporting Information Figure S3C,D). More specifically, high VNN1 expression at diagnosis associated with a higher frequency of patients with minimal residual disease (MRD) and refractory disease or relapse (Ref/Rel), and a lower amount of patients in complete remission (CR), after the first and second induction cycles and during follow-up and subsequent treatments (Figure 1B). We also observed a significantly higher percentage of death within 60 days from the first treatment (an indicator of therapeutic failure)1 in the VNN1-high group as compared to the VNN1-low group (Figure 1C). Evaluation of the response rate (the % of patients in complete remission) shows that high VNN1 expression only marginally reduces the success rate of the first complete therapeutic cycle (from Induction1-Ind1 to first consolidation-Ind3/Con1), but it significantly lowers the amount of patients who remain in CR at subsequent time points (from Ind3/Con1 to last consolidation and follow-up -Con3/Last), eventually reducing the overall therapeutic success (from Ind1 to Con3/Last) (Figure 1D). Finally, we investigated a vast range of possible genetic defects and transcriptional events which could potentially alter VNN1 expression but we found no alteration in the gene or its transcription, neither in TCGA LAML or ICGC AML cohorts nor in AML cell lines from the COSMIC repository (Supporting Information Table S4). Furthermore, even though VNN1 is part of the leukemia stem cell (LSC) signature identified by Gentles et al.,4 we did not find any association between VNN1 and this signature (P: 0.298 for TCGA LAML, 0.999 for GSE10358 and 0.571 for TARGET-AML, Fisher's Exact). Based on these results, we hypothesized that one or more gene regulatory networks (GRN) might specifically control VNN1 expression, and tested this hypothesis in both Aracne5 and a neural-network algorithm for the identification of differentially-expressed GRN developed by us. In both cases we identified a common GRN in which HOXB5 and IL2RA (already implicated in AML and LSC resistance to chemotherapy)6 are regulators of VNN1. Notably, the expression of HOXB5 was linearly associated with VNN1 in all tested cohorts and that of IL2RA in three out of four cohorts (Supporting Information Figure S4), strongly suggesting that this GRN is implicated in controlling VNN1 expression. Concluding, our data extend previous reports on VNN1 importance in AML and suggest that VNN1 expression is a reliable marker to identify AML patients at risk of relapse and poor outcome. The authors thank Jaana Peters and Kirsi Kvist-Mäkelä for technical assistance and the CSC - IT Center for Science Ltd. for Chipster software and technical support. This work was supported by the Centre of Excellence Grant 2012–2017 of the Academy of Finland (284605), the Sigrid Jusélius Foundation, the Finnish Cancer Foundation and the University of Oulu Graduate School. The authors declare no conflict of interest. VI developed the research, performed analyses and wrote the manuscript; JL and RD performed RT-qPCR and analyses, ERS and PK assembled the Oulu retrospective cohort and performed analyses; RH and TP developed the research and wrote the manuscript. Additional Supporting Information may be found online in the supporting information tab for this article. 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