Identification of novel biomarkers for MLL-translocated acute myeloid leukemia

Accepted Manuscript Title: Identification of novel biomarkers for MLL translocated acute myeloid leukemia Author: Karine Lagacé, Fréderic Barabé, Josée Hebert, Sonia Cellot, Brian T. Wilhelm PII: DOI: Reference:

S0301-472X(17)30758-0 http://dx.doi.org/doi: 10.1016/j.exphem.2017.08.006 EXPHEM 3571

To appear in:

Experimental Hematology

Received date: Revised date: Accepted date:

19-7-2017 25-8-2017 28-8-2017

Please cite this article as: Karine Lagacé, Fréderic Barabé, Josée Hebert, Sonia Cellot, Brian T. Wilhelm, Identification of novel biomarkers for MLL translocated acute myeloid leukemia, Experimental Hematology (2017), http://dx.doi.org/doi: 10.1016/j.exphem.2017.08.006. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Identification of novel biomarkers for MLL translocated acute myeloid leukemia

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Karine Lagacé , Fréderic Barabé

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, Josée Hebert , Sonia Cellot , Brian T Wilhelm

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CHU de Québec Hôpital Enfant-Jésus; Quebec City, Quebec, Canada;

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Department of Medicine, Université Laval, Quebec City, Quebec, Canada,

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Category: Malignant Hematopoiesis

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Word count : 1929

Laboratory for High throughput biology, Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, QC, Canada Centre de recherche en infectiologie du CHUL, Centre de recherche du CHU de Québec, Quebec City, Quebec, Canada,

Division of Hematology-Oncology and Leukemia Cell Bank of Quebec, Maisonneuve-Rosemont Hospital, Montréal, QC, Canada, Department of Medicine, Université de Montréal, Montréal, QC, Canada.

Department of pediatrics, division of Hematology, Ste-Justine Hospital, Montréal, QC, Canada, Université de Montréal, Montréal, QC, Canada,

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*Correspondence to: Brian Wilhelm Institute for Research in Immunology and Cancer Université de Montréal P.O. Box 6128, Station Centre-Ville Montreal, Québec, Canada H3C 3J7 Phone : +1 514 343.6111 ext 0923 Fax : +1 514 343.7780 E-mail : [email protected]

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Highlights

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1) Human model AMLs has allowed the identification of new biomarkers for MLL-AML

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2) qRT-PCR tests validate MLL-specific and pan-AML expression biomarkers

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3) The novel biomarkers provide a more sensitive assay than current tests

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Abstract

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Acute myeloid leukemias (AML) with translocations of the Mixed Lineage Leukemia

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(MLL/KMT2A) gene are common in young patients and are generally associated with

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poor clinical outcomes. The molecular biology of MLL fusion genes remains incompletely

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characterized and is complicated by the fact that over 100 different partner genes have

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been identified in fusions with MLL. The continually growing list of MLL fusions also

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represents a clinical challenge with respect to identification of novel fusions and tracking

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the fusions to monitor progression of the disease after treatment. We have recently

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developed a novel single donor model leukemia system that permits the development of

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human AML from normal cord blood cells. Gene expression analysis of this model and

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MLL-AML patient samples has identified a number of candidate biomarker genes with

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highly biased expression on leukemic cells. Here we present the data demonstrating the

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potential clinical utility of several of these candidate genes for identifying known and

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novel MLL fusions.

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Introduction

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Chromosomal translocations involving the MLL (KMT2A) gene (11q23) are

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among the most common genetic aberrations in pediatric acute myeloid leukemia (AML)

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(~13%) [1] and are associated with intermediate to poor prognosis depending on the

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specific fusion partner gene [2]. Screening tools to detect MLL-rearranged AML are

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therefore extremely valuable in the clinical setting to guide molecular classification. Most

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clinical laboratories perform MLL break apart FISH (fluorescent in situ hybridization)

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techniques [3] to screen for MLL-AML, while karyotype or RT-PCR using specific primers

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allow for the identification of the specific MLL fusion partner, which is critical for risk

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stratification and for monitoring residual disease after treatment (minimal residual

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disease, MRD). The diagnosis of MLL translocations represents a clinical challenge

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since more than 100 different partner genes have been found fused to MLL [4]. In

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addition, some of the resulting fusions can be cryptic, complicating the development of

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fusion-specific molecular assays by standard cytogenetic techniques. In this context, the

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development of small panels of genes that are specifically overexpressed in MLL-AML

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would contribute to streamline the detection of MLL-AML cases at diagnosis and

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potentially to track molecular MRD when tumor burden is low, where sensitive and

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specific assays are required. MRD tracking by flow cytometry in AML is currently

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associated with a 20-40% rate of false negative results [5], prompting the elaboration of

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improved strategies to follow treatment response. Through the development of single

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donor human AML models [6], and their comparison to MLL-AML patients, we have

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identified a set of genes with high, and leukemia biased, expression relative to normal

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blood cells. Here we report on the use of 7 of these genes to define a molecular

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signature that has potential clinical utility for the diagnosis of MLL-translocated AMLs.

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Methods

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Patient and normal samples

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All pediatric and adult AML patient samples and additional clinical information

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used in this study were collected by the Banque de cellules leucémiques du Québec

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(BCLQ) with informed consent and project approval from the Research Ethics Boards of

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CHU Ste-Justine, Maisonneuve-Rosemont Hospital and Université de Montréal.

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Peripheral blood and bone marrow samples were collected from healthy donors under

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informed consent.

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Identification of candidate genes

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A list of 39 MLL-AF9 AML specific genes was previously identified using a human

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leukemia model, as described in Barabé et al. [6]. Briefly, cord blood stem cells from

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single healthy donors were transduced with a retrovirus expressing the MLL-AF9 (MA9)

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fusion gene. Transduced cells were expanded in vitro and injected into NSG

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immunodeficient mice to generate multiple human leukemias, arising from the same

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donor genetic background. In order to identify changes in gene expression level taking

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place during leukemogenesis, RNA-Seq was performed (as described [6]) on samples

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from each stage of leukemia development (healthy CD34+, CD34++ MLL-AF9 and model

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AMLs). A data filtering strategy was developed to identify genes expressed specifically in

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MA9-AML (RPKM >3) but not expressed (RPKM < 1) in normal tissues and other AML

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samples which have no MLL translocations. From the 39 candidate genes identified, 7

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were selected for the testing as potential diagnostic tools based on their overall

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expression level, and expression pattern in leukemia and normal tissues.

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RNA isolation, cDNA synthesis and qRT-PCR

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Total RNA was extracted from AML and normal samples using TRIzol reagent

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(Invitrogen). RNA was treated with DNase prior to being reverse transcribed using a mix

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of random primers and oligo d(T) using the QuantiTect Reverse Transcription kit

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(QIAGEN) as described by the manufacturer. Samples were diluted 1:3 prior to use for

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qRT-PCR and gene expression was determined using custom TaqMan qPCR assays

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(IDT) (Supplementary Tables 3, 4). The amplification efficiency of each qRT-PCR assay

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was validated in triplicate using tenfold serial dilutions of each target gene over 5 orders

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of magnitude in parallel with serial dilutions of the control gene (ABL1). qRT-PCR

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reactions were performed using PerfeCTa® qPCR FastMix II (Quanta Biosciences), 0.5

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µM of each primer and 0.25 µM of each probe on a Viia7 instrument (Life Technologies)

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at the IRIC genomics platform. Amplification was programmed with an initial step of 20

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sec at 95˚C, followed by 40 cycles of: 1 sec at 95˚C and 20 sec at 60˚C. Relative

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expression was calculated using the comparative CT method (2-CT) and normalization

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was done using ABL1 reference gene with each PCR reaction performed in duplicate.

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MRD assay sensitivity

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The MRD assay sensitivity was tested by serially diluting cDNA from MA9

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patients in healthy bone marrow cDNA over 6 orders of magnitude (from 10 0 down to 10-

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). qPCR experiments were performed in duplicates as described above.

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Results and discussion

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We have previously developed a xenograft model system, using single human

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donors, to generate acute myeloid leukemias [6]. Using RNA-seq data from this model,

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combined with AML patients harbouring an MLL-AF9 (MA9) translocation, we sought to

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identify potential novel biomarkers for this subgroup of AMLs. The selection of genes

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consistently expressed in MA9-AMLs but not expressed in normal CD34+ cells,

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mononuclear cells and B-cell acute lymphoblastic leukemias (B-ALL) generated by our

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model, revealed 39 potential biomarker genes [6] (Fig. 1A). While these genes were

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initially identified using MA9-AMLs, in fact many of these candidate genes are also

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expressed in other AMLs with or without MLL fusions. Most of these genes have been

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studied in other contexts (Supplementary Table 1), but to date, none have been

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associated with a pathophysiological role in acute myeloid leukemia. From these 39

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genes, 7 were selected based on their differential expression patterns in leukemic cells

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and normal tissues (RET is shown as an example in Fig 1b) to design a qRT-PCR

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diagnostic assay.

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To evaluate the potential of these candidate genes as diagnostic targets, their

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expression level was first assayed by qRT-PCR using a cohort of 87 AML patients and

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14 healthy donors (Supplementary Table 2). Relative expression values were calculated

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and compared between defined cytogenetic groups including MLL-rearranged, normal

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karyotype, Monosomy 5/5q- and 7/7q-, intermediate abnormal karyotype and complex

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karyotype. To examine the influence of the source of normal blood cells on the

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expression level of our genes, we also analyzed 3 samples of peripheral blood (PB), 3

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fresh bone marrow (BM) and 8 frozen bone marrow from different healthy donors.

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Our results confirmed that all 7 candidate genes were highly upregulated in

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patients with MLL rearrangement compared to other cytogenetic subgroups and normal

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bone marrow (Fig. 1C, Supplementary Fig. 1). Because of its high expression level,

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PPP1R27 was the most promising target, being expressed around ~100 times higher on

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average in MLL-rearranged leukemias than in control BM (Fig. 1C). When focusing on

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MLL translocations organized by fusion partner, we found that our potential biomarkers

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were upregulated in the vast majority of MLL fusion subgroups, except for MLL-GAS7,

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for which all candidate genes but NRG4 were expressed at a lower or similar level to BM

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(Supplementary Fig. 2). These results suggest that our candidate genes are suitable

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biomarkers for clinical diagnostic of most MLL leukemias, with some rare exceptions.

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Importantly, these results also clearly demonstrate that the downstream transcriptional

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targets of MLL translocations, whether direct or indirect, have the potential to simplify the

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diagnostic tests for a broad range of known or novel fusions. Moreover, the candidate

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gene NRG4 was upregulated in all AML patients, regardless of the cytogenetic subgroup

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(Fig. 1C), suggesting that this target could be suitable for a “pan-AML” diagnostic test.

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With respect to the expression of the candidate genes in the normal control cells,

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although a slight difference was observed between fresh and frozen BM samples, the

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expression values were generally comparable. As expected, due to the higher frequency

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of normal progenitor cells, we found that the expression level of the candidate genes

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was generally higher in BM than in PB. The abundance of leukemia-specific transcripts

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is thus generally higher in bone marrow than blood, particularly in the context of low

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tumor burden following chemotherapy [7]. For this reason, the mean value of fresh BM

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samples was used as the reference level of expression for our experiments, although

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detection levels in PB were clearly more sensitive.

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To further validate our findings with an external cohort, we used the RNA-Seq

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data from the TARGET pediatric AML cohort [8]. When grouped by FAB classification,

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there was a significantly higher expression of our candidate genes in M5 AMLs,

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characteristic of patients with MLL translocation (Supplemental Fig. 3A). Samples with

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the reported presence of MLL translocation showed also an enrichment of the

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biomarkers (Supplemental Fig. 3B). In addition, analysis of patients with high expression

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of both of these markers identified ~76% of the MLL-positive patients in the cohort

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(Supplemental Fig. 4). These results support our observation that these genes highlight

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a large majority of MLL-translocated samples.

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Given the specificity of our candidate genes, we next wanted to investigate their

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performance relative to the current clinical standard tracking the expression level of the

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fusion gene. We therefore compared the expression level of the candidate genes to the

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fusion transcripts in several MLL-rearranged subgroups using two approaches, RNA-seq

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and qRT-PCR. Previous RNA-Seq data of 13 AML patients expressing the MLL-AF9

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translocation [10] suggested that most of our candidate genes are generally expressed

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at higher levels (~20-150x) than the fusion gene (Fig. 2A). To confirm these data by

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qRT-PCR, primers spanning the fusion junction were designed to measure the

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expression level of the fusion gene in two or three samples of the most frequent MLL

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translocation subgroups (Fig. 2B). For patients with MLL-AF6, MLL-ENL and MLL-ELL

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fusions, we found that the expression level of the four tested candidate genes was

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similar to the corresponding fusion. However, in MLL-AF9 cases, the four candidates

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were expressed 4-80 times higher than the MLL-AF9 fusion transcript. Similar results

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were observed in patients harbouring the MLL-AF10 translocation, except for SCUBE1,

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which had comparable expression to the fusion. For diagnostic purposes, targeting the

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candidate genes in these cases would provide a more sensitive assay than tracking the

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expression of the fusion alone. Importantly, the expression of our biomarker genes is

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stable between diagnostic and relapse samples (Supplementary Fig. 5), indicating that

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they have utility throughout the course of treatment. Additionally, because MLL-AF9 and

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MLL-AF10 fusions represent together ~50% of all MLL translocations found in the

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pediatric AML population and 37% of adult MLL-AML patients [11], use of these genes

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as diagnostic targets could potentially benefit a large proportion of patients. Specifically,

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qRT-PCR performed using the 2 most sensitive genes (PPP1R27, CCL23) would allow

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the rapid identification of samples with potential MLL fusions, including potentially

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novel/cryptic fusions, or in samples with complex karyotypes [8].

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The monitoring of minimal residual disease (MRD) to assess treatment response

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is of significant importance for risk stratification and early detection of relapse [12]. In

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AMLs harboring chromosomal translocations such as MLL rearrangements, the fusion

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transcripts are currently used in the clinic for MRD detection, mostly because fusion-

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based MRD measurements are among the most sensitive methods available. The

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sensitivity varies depending on the number of fusion transcripts per leukemic cell, but

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typically reaches 1×10−5 (1 leukemic cell in 100,000 normal cells) [13]. To test whether

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any of our candidate genes might be useful in the context of MRD testing, we performed

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qRT-PCR assays using tenfold serial dilutions of AML cDNA added to healthy bone

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marrow cDNA. The test results did not demonstrate greater sensitivity compared to

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standard clinical MRD detection assays used, with the sensitivity of our assays ranging

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between 10-1 and 10-3. These results likely reflect that our candidate genes, while biased

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towards significantly higher expression in AMLs, are nevertheless expressed at low

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levels in normal bone marrow and blood.

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Conclusion

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While FISH and RT-PCR diagnostic methods currently in place to screen for MLL

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rearrangements have good sensitivity, their technical limitations mean that they are not

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as useful for patients who have less frequent or novel fusion breakpoints or some cryptic

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translocations. We have shown in this study that measuring the expression level of MLL-

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AML biomarkers could provide a simple and reliable diagnostic method for AML patients

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with MLL rearrangements. We have also shown that in many cases our candidate genes

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have generally higher expression levels than the fusion genes, allowing a more sensitive

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detection. The method described in this study could provide a quick and cost-effective

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screen of MLL status in routine referrals.

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Acknowledgments:

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This work was supported by a Terry Fox New Investigator grant (1042-BTW and 1043-

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SC) including funding from the Cole Foundation (BTW, SC), the Fonds de Recherche du

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Québec en Santé (BTW), La Fondation du Centre de Cancérologie Charles Bruneau

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and La Fondation CHU Sainte-Justine (SC). Human leukemia specimens were collected

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and analyzed by the Banque de cellules leucémiques du Québec (BCLQ), supported by

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the Cancer Research Network of the Fonds de Recherche du Québec en Santé (FRQS).

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References

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Grimwade, D. and S.D. Freeman, Defining minimal residual disease in acute myeloid leukemia: which platforms are ready for "prime time"? Blood, 2014. 124(23): p. 3345-55. Slany, R.K., The molecular mechanics of mixed lineage leukemia. Oncogene, 2016. 35(40): p. 5215-5223. Wolff, D.J., et al., Guidance for fluorescence in situ hybridization testing in hematologic disorders. J Mol Diagn, 2007. 9(2): p. 134-43. Meyer, C., et al., The MLL recombinome of acute leukemias in 2013. Leukemia, 2013. 27(11): p. 2165-76. Paietta, E., Minimal Residual Disease in AML: Why Has It Lagged Behind Pediatric ALL? Clin Lymphoma Myeloma Leuk, 2015. 15 Suppl: p. S2-6. Barabe, F., et al., Modeling human MLL-AF9 translocated acute myeloid leukemia from single donors reveals RET as a potential therapeutic target. Leukemia, 2017. 31(5): p. 1166-1176. Hills, R.K., et al., Assessment of Minimal Residual Disease in Standard-Risk AML. N Engl J Med, 2016. 375(6): p. e9. Farrar, J.E., et al., Genomic Profiling of Pediatric Acute Myeloid Leukemia Reveals a Changing Mutational Landscape from Disease Diagnosis to Relapse. Cancer Res, 2016. 76(8): p. 2197-205. Lemieux, S., et al., MiSTIC, an integrated platform for the analysis of heterogeneity in large tumour transcriptome datasets. Nucleic Acids Res, 2017. 45(13): p. e122. Lavallee, V.P., et al., The transcriptomic landscape and directed chemical interrogation of MLL-rearranged acute myeloid leukemias. Nat Genet, 2015. 47(9): p. 1030-7. Krivtsov, A.V. and S.A. Armstrong, MLL translocations, histone modifications and leukaemia stem-cell development. Nat Rev Cancer, 2007. 7(11): p. 823-33. Ommen, H.B., Monitoring minimal residual disease in acute myeloid leukaemia: a review of the current evolving strategies. Ther Adv Hematol, 2016. 7(1): p. 3-16. Gabert, J., et al., Standardization and quality control studies of 'real-time' quantitative reverse transcriptase polymerase chain reaction of fusion gene transcripts for residual disease detection in leukemia - a Europe Against Cancer program. Leukemia, 2003. 17(12): p. 2318-57.

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Figure legends

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Figure 1 - Identification and validation of candidate genes by leukemia subgroup.

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(A) Schematic representation of the data filtering strategy used to identify candidate

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MLL-AF9 biomarker genes. (B) Boxplots of gene expression data (RPKM) for RET are

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shown from NK-AMLs (pink), CD34+ cells, and MLL translocated patient or model AMLs;

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red) and from a variety of normal tissues (GTEx; green) (C) The expression level of

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candidate genes (log10 of qRT-PCR values relative to ABL1) that are either specific for

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MLL translocated AML (PPP1R27) or that are expressed in most AMLs (NRG4) are

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shown. AML subgroups (MLL= MLL translocated, NK-AML=normal karyotype,

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Mono7=monosomy 7, Int=Intermediate cytogenetic risk, Complex=complex karyotype)

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are shown along the x-axis. Normal controls from peripheral blood (PB), fresh bone

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marrow (BM), or previously frozen bone marrow (BM-Frozen) are shown in green. The

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mean value of the BM group is shown as a reference level of expression (green

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horizontal dotted line). The bottom panel shows expression level of all MLL translocated

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is shown, organized by the fusion partner genes involved (x-axis).

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Figure 2 – RNA-seq and qRT-PCR of candidate genes vs gene fusion. (A) RNA-seq

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expression data is shown for four candidate genes (red dots) and for the two genes

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involved in the fusion gene in those specific patients (dark/light green dots). (B) qRT-

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PCR was performed in AML patients with different MLL fusions using primers specific for

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candidate genes (coloured forms) or spanning the fusion gene in each patient (black *

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shape).

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Supplemental figure 1 – Identification and validation of additional candidate genes

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by leukemia subgroup. The expression level of seven candidate genes (log10 of qRT-

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PCR values relative to ABL1) are shown, grouped by cytogenetic classification. Patient

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sample colouring, AML subgroups and dotted line are as shown in Figure 1, top panel.

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Supplemental figure 2 – Expression of candidate genes by MLL fusion genes. The

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expression level of seven candidate genes (log10 of qRT-PCR values relative to ABL1)

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are shown, grouped by MLL fusion genes present. Patient sample colouring, AML

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subgroups and dotted line are as shown in Figure 1, bottom panel.

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Supplemental figure 3 – External validation using TARGET pediatric AML data.

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The expression level of two of our candidate genes in the TARGET pediatric AML cohort

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[8] (n=358) are shown with the data grouped by FAB classification (A) or by the reported

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presence/absence of MLL translocations (B). The mean expression of the candidate

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genes is significantly different between patients with/without MLL fusions.

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Supplemental figure 4 – Paired gene expression in MISTiC. TARGET gene

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expression data and clinical annotation was loaded into a local instance of the MISTiC

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tool [9] and correlation between gene expression was examined for two candidate genes

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(PPP1R27 and PHACTR3). Selection of patient samples with high expression of both of

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these genes (~23% of the cohort) results in the identification of 39/51 (~76%) of samples

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with an MLL fusion which represents a statistically significant enrichment (p = 3.5e-18).

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Supplemental figure 5 – Expression of candidate genes in paired diagnostic and

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relapse samples. RNA-seq data from diagnostic and relapse samples from two adult

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AML patients with MLL-AF9 fusions was analyzed. Expression levels of four candidate

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genes are shown on the left while the two partners of the gene fusion are shown on the

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right. Solid line shown the expression of the diagnostic (D) samples while dotted lines

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shown the relapse (R) samples.

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