Genetic Analysis Using a High Density SNP Array in Myelodysplastic Syndrome: Clinical Utility and Comparative Analysis Study Compared to Metaphase Chromosome Analysis
Authors: Jeffries Sally , Trim Nicola , Huxley Emma , Ford Laura , Raghavan Manoj , Soden Jane , Griffiths Michael John 
Published: November 2019

Abstract
There is no single technology capable of detecting the various genetic and genomic aberrations observed in patients with neoplasia. Patients with myelodysplastic syndrome (MDS) may present with chromosomal copy number changes (duplication, deletion, and amplification), balanced chromosome rearrangements, copy neutral loss of heterozygosity (CN-LOH) and/or gene mutations. Currently only microscopic chromosomal changes, as dictated by the international prognostic scoring system (IPSS-R), are used to determine the genetic risk in MDS. However, different genetic aberrations, particularly gene mutations are anticipated to be incorporated into the IPSS-R in the near future. The Affymetrix CytoScan® HD Array is a high definition array with over 2.6 million markers (both copy number and SNP) allowing resolution capabilities way beyond that of metaphase chromosome analysis.
The incorporation of 750,000 SNPs also allows for detection of CN-LOH, regions known to harbour bi-allelic gene mutations. A real-time comparative study using the Affymetrix CytoScan® HD Array against traditional metaphase chromosome analysis is being performed on patients with confirmed or highly suspected MDS referred for genetic analysis at the West Midlands Regional Genetics Laboratory, UK. The study is expected to utilise 600 arrays over two years at presentation and on serial surveillance samples. The preliminary results available after the first 100 patients are presented with examples demonstrating the capabilities and clinical utility of SNP array genetic analysis.
The study so far, in patients with MDS at presentation, has demonstrated: An increased number of genetic aberrations (CN changes and CN-LOH) detected by SNP array (38/105 (36%) by metaphase analysis and 62/105 (60%) by SNP array analysis).The ability to reliably detect deletions at the single gene level including CUX1, TET2 and RUNX1, and rarely copy number changes within genes including duplication within KMT2A, consistent with partial tandem duplication.The detection of CN-LOH regions, which may contain bi-allelic gene mutations, in 20/105 (19%) of cases, including chromosomal regions 1p (MPL, NRAS), 4q (TET2), 7q (CUX1), 11q (CBL), 17p (TP53). Confirmatory studies are on-going.A lower failure rate for SNP array compared to metaphase analysis (1% v 4%). Of the four failed metaphase cases, three showed recurrent genetic aberrations observed in MDS including del(5q), del(20q) with CN-LOH 17p, and trisomy 8. The failed SNP array had a normal karyotype.Confirmed balanced rearrangements (without gain or loss of genetic material) are not detected.The ability to detect abnormal clones with copy number changes (deletion or gain at one or more loci) at sensitivities as low as between 5 and 20% dependent on aberration size.Twenty-two cases with a normal karyotype had abnormal genetic aberrations detected by SNP array. Two cases with an abnormal karyotype had a normal SNP array profile due to a balanced rearrangement and a low level abnormal clone (4%) beyond the sensitivity of the test.The ability to utilise peripheral blood instead of marrow as no dividing cells are required, thereby allowing genetic analysis in patients too frail or otherwise unsuitable for marrow aspirationThe ability to detect deletion or CN-LOH of the HLA gene region, which is critical in patients being considered for stem cell transplant as HLA typing may be inaccurate or ambiguous.The ability when performed as a complementary tool to metaphase analysis to detect sub-clones or concurrent clonal neoplasia with different copy number changes.
Patient benefits are expected to be the potential to improve patient outcomes through improved confidence in diagnosis, prognosis and monitoring.

Disclosures
Jeffries: Affymetrix: Research Funding.