Abstract 2416: Transcriptome and cluster analysis of infant acute lymphoblastic leukemia cases with and without MLL (KMT2A) rearrangement
Authors: Yoo Byunggil , Farooqi Midhat S. , Kostadinov Rumen , Miller Neil , Johnston Jeff , Farrow Emily , Kelley Shannon , Gibson Margaret , Brown Patrick , Guest Erin 
Published: July 2017

Background: Infant acute lymphoblastic leukemia (ALL) is a high-risk cancer with poor survival due to treatment failure and relapse. The majority of infant ALL cases possess an MLL (KMT2A) translocation (MLL-R), where MLL joins with AF4 (AFF1), ENL (MLLT1), or another partner gene to create a novel fusion gene. A subset of infant ALL cases do not involve an MLL rearrangement (non-MLL-R). Gene expression profiling delineates MLL-R from non-MLL-R cases. Here, we describe transcriptome profiling and cluster analysis of MLL-R and non-MLL-R cases and compare between partner genes.

Methods: We performed RNA sequencing (RNA-seq) on diagnostic blood or bone marrow samples from 40 infants with ALL. Cohort A included 16 patients with MLL-R ALL known to have relapsed; cohort B, 10 patients with MLL-R ALL not known to have relapsed; and cohort C, 14 patients with non-MLL-R ALL whom to date have also not relapsed. RNA-seq was performed to an average of 8.8Gb and analyzed using Bowtie2, RSEM, and limma-voom. Multiple different groups of cases (e.g. cohort A versus B) were compared for differential gene expression; the resulting genes were ranked by adjusted P value with a significance cutoff of 0.01 and further evaluated for pathway analysis with Ingenuity software. Hierarchical clustering of samples was conducted using distance measures computed from normalized gene expression.

Results: Transcriptome analysis of MLL-R versus non-MLL-R cases found 2,334 differentially expressed genes. Ingenuity pathway analysis of these genes showed enrichment in specific gene sets, such as those involved in PTEN, EGF, and NF-κB signaling. Ingenuity predicted increased PTEN signaling and diminished EGF and NF-κB signaling in MLL-R cases relative to non-MLL-R cases. Transcriptome analysis of relapsed versus non-relapsed MLL-R cases found no differentially expressed genes meeting significance criteria, while analysis of MLL fusion partners identified 46 differentially expressed genes including BMI1 and MYC. Cluster analysis demonstrated a distinct grouping of non-MLL-R cases relative to MLL-R cases. Additionally, MLL-R samples sub-clustered according to their MLL fusion gene partners. However, no difference in clustering was appreciated between MLL-R cases that later went on to relapse versus those that did not.

Conclusions: Our findings show that MLL-R infant ALL has a distinct gene expression signature at diagnosis that correlates with the type of MLL translocation present. This is important because it suggests treatment strategies could be tailored to the MLL partner gene. Risk of relapse in MLL-R cases could not be predicted by this signature due to a paucity of differentially expressed genes between relapsed and non-relapsed groups at diagnosis. Similar to prior profiling studies, we find that non-MLL-R cases independently cluster together and have a gene expression signature distinct from MLL-R cases.[B.Y. and M.F. contributed equally to this work.]

Citation Format: Byunggil Yoo, Midhat S. Farooqi, Rumen Kostadinov, Neil Miller, Jeff Johnston, Emily Farrow, Shannon Kelley, Margaret Gibson, Patrick Brown, Erin Guest. Transcriptome and cluster analysis of infant acute lymphoblastic leukemia cases with and without MLL (KMT2A) rearrangement [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2416. doi:10.1158/1538-7445.AM2017-2416