The Identification of Further Minimal Regions of Overlap in Chronic Lymphocytic Leukemia Using High-Resolution SNP Arrays
Authors: Knight Samantha JL , Clifford Ruth , Robbe Pauline , Ramos Sara DC , Burns Adam , Timbs Adele T , Alsolami Reem , Weller Susanne , Hamblin Angela , Mason Joanne , Oates Melanie , Titsias Michalis , Yau Christopher , Holmes Chris C , Pettitt Andrew R , Hillmen Peter , Taylor Jenny , Shuh Anna 
Published: October 2019

Abstract
Background:Historically, the identification of minimal deleted regions (MDRs) has been a useful approach for pinpointing genes involved in the pathogenesis of human malignancies and constitutional disorders. Microarray technology has offered increased capability for newly identifying or refining existing MDRs and minimal overlapping regions (MORs) in cancer. Despite this, in chronic lymphocytic leukemia (CLL), published MORs that pinpoint only a few candidate genes have been limited and with the advent of NGS, the utility of high resolution array work as a discovery tool has become uncertain. Here, we show that profiling copy number abnormalities (CNAs) and cnLOH using arrays in a large patient series can still be a valuable approach for the identification of genes that are disrupted or mutated in CLL and have a role in CLL development and/or progression.
Methods: 250 CLL patient DNAs from individuals enrolled in two UK-based Phase II randomised controlled trials (AdMIRe and ARCTIC trials) were tested using Infinium HumanOmni2.5-8 v1.1 according to manufacturer’s guidelines (Illumina Inc, San Diego, CA). Data were processed using GenomeStudioV2009.2 (Illumina Inc.) and analysed using Nexus Discovery Edition v6.1 (BioDiscovery, Hawthorne, CA). All Nexus plots were inspected visually to verify calls made, identify uncalled events and exclude likely false positives. To exclude common germline CNVs, the Database of Genomic Variants (DGV), a comprehensive catalog of structural variation in control data, was used. Copy number (CN) changes that encompassed fully changes noted in the DGV were excluded from further analysis. Regions of copy neutral loss of heterozygosity (cnLOH) were recorded if >1Mb in size, but were not used to define or refine MORs. Data from 1275 age-appropriate control samples minimised the reporting of common cnLOH events. All genomic coordinates were noted with reference to the GRCh37, hg19 assembly. MORs were investigated using Microsoft Excel filtering functions. A subset of genes (n=91) selected from MORs mainly on the basis of event frequency and/or number of genes within the MOR and/or literature interest were taken forward for targeted sequencing (exons only) of appropriate samples with/without CN Losses or cnLOH (Set 1 n=124; Set 2 n=126). These were tested using custom designed TruSeq Custom Amplicon panels (Illumina Inc) and processed according to manufacturer’s instructions. SAMHD1 was excluded from these panels since it had been studied separately within our laboratory. The data were analysed using an in-house bioinformatics pipeline that uses the sequence aligners MSR and Stampy and the variant callers GATK and Platypus, followed by stringent filtering.
Results: Using our datasets we have identified >50 MORs previously unreported in the literature. Six of these showed copy number (CN) losses in >3% of patients studied. Furthermore, we have refined 14 MORs that overlapped with regions described previously and that had also a CN loss frequency of >3%. Thirteen MORs involved only a single reference gene, often a gene implicated previously in cancer (eg. SAMHD1, MTSS1, DCC and RFC1). Of the 91 genes taken forward for targeted sequencing, stringent data filtering led to a subset of 19 genes of interest harbouring exonic mutations. Genes with mutations identified include DCC, BAP1 and FBXW7, also implicated previously in cancer.
Conclusion: We have generated high resolution CNA and cnLOH profiles for 250 first-line chemo-immunotherapy treated CLL patients and used this information to document newly identified MORs, to refine MORs reported previously and to identify mutation harbouring genes using targeted NGS. Functional knowledge supports our hypothesis that these genes may have a contributory role in CLL. For two genes, SAMHD1 and FBXW7, relevance in CLL has been established already. Taken together, our data validate the utility of high resolution arrays studies for the identification of candidate genes that may be involved in CLL development or progression when disrupted. Further studies are required to confirm a role for these genes in CLL and to elucidate the nature of the underlying biological mechanisms.

Disclosures
No relevant conflicts of interest to declare.