Analysis of the Coding Genome of Follicular Lymphoma Identifies Multiple Novel Recurrently Mutated Genes
Authors: Malek Sami , Li Yifeng , Li Hongxiu , Ouillette Peter , Jones Sian , Fox Heather , Jacobi Kathryn , saiya-Cork Kamlai , Bixby Dale , Lebovic Daniel , Shedden Kerby , Sabel Michael , Marentette Lawrence , Cimmino Vincent , Chang Alfred , Kaminski Mark S. 
Published: October 2019

Abstract 147

Introduction:

Follicular lymphoma (FL) constitutes the second most common non-Hodgkin's lymphoma in the Western world. FL carries characteristic recurrent structural genomic aberrations. However despite recent advances, knowledge regarding the coding genome in FL is still evolving and currently incomplete.

Methods:

To further our understanding of the genetic basis of Follicular Lymphoma (FL), we used solution exon capture of sheared and processed genomic DNA isolated from FACS-sorted lymphomatous B-cells and paired CD3+ T-cells isolated from eleven cases of FL and one case of DLBCL transformed from prior FL followed by paired-end (96 base pair read length per side) massively parallel sequencing. Data from three independent HiSeq2000-based runs were pooled to maximize coverage. The sequence data were characterized by excellent technical QC parameters including a depth of coverage range of 43–73 and with 90% of bases in the target region covered by at least 10 reads. Data were subsequently analyzed using a validated bioinformatics pipelines (Personal Genome Diagnostics Inc., Baltimore, Maryland) serving as the primary data source to nominate candidate mutated genes. To complement the next gen sequencing data, we analyzed the 12 FL cases that constituted the discovery cohort for next generation sequencing for acquired genomic copy number aberrations (aCNA/LOH) and acquired uniparental disomy (aUPD) using SNP 6.0 array profiling. Data for paired DNA samples (sorted FL B-cells versus CD3 cells) were analyzed using dChip-based visual and algorithmic data analysis methods.

Results:

The bioinformatics pipeline nominated between 13 and 86 (mean of 47) somatically mutated genes per FL case; of these, 480 represented distinct genes. Importantly, 32 genes were nominated to be mutated in ≥2 out of 12 cases and all these candidate recurrent gene mutations and various other genes for a total of N=122 genes were subjected to Sanger sequence validation. Overall, we validated 68 genes as mutated in at least 1/12 FL discovery set cases. These included frequent mutations in MLL2 (8/12), CREBBP (7/12) and BCL2 (5/12). In addition, we identified 19 novel recurrently mutated genes (≥2 out of 12 FL cases with mutations). From these 19 genes and functionally related genes we selected 10 genes for a complete mutation analysis in a total 57 FL cases. Within the group of recurrently mutated genes we have identified a gene involved in apoptosis threshold regulation as well as multiple novel genes involved in B-cell transcriptional control. Further, we identify frequent mutations in the linker Histone genes HIST1H1 B-E. Finally, through incorporation of SNP array profiling data, we identify multiple candidate target genes for frequent aUPD in FL and further a list of single mutated genes (PTEN, A20, ARID1A, VAV1, TLR2 and TLR8 and others) that can be directly implicated in the pathogenesis of afflicted FL cases.

Conclusion:

This large genomic profiling study identifies 19 novel recurrently mutated genes in FL, including an apoptosis regulator, transcription factors and linker histones, thereby substantially broadening our understanding of the genetic basis of FL.

Disclosures:

Lebovic: Genentech: Speakers Bureau.