Genomic Diversity of Newly Diagnosed Follicular Lymphoma: a Pilot Investigation

To date, whole genome and exome sequencing studies of follicular lymphoma (FL) have primarily focused on identification of small site mutations that are recurrent in FL tumorigenesis or involved in tumor clonal evolution. A comprehensive genomic and transcriptomic survey of various mutation types including large structural variants (SVs) in FL cases with detailed clinical annotations and long-term follow-up has not been accomplished.

To gain insight into genetic biomarkers that may predict clinical features, we performed exome and whole genome mate-pair sequencing of fresh frozen tumor and paired peripheral blood DNAs, and transcriptome sequencing of tumor RNAs, from 8 FL patients. The patients we selected were either below the median age of FL onset (n=7, median 54.5 yrs) or had a family history of lymphoma (n=1). These patients were clinically diverse, and included patients who had Grade 1 or 2 disease (n=4), classified as “indolent”; and patients with Grade 3a disease (n=2) or who subsequently had pathologic transformation (n=2), classified as “aggressive”.

The coding regions of the genome (exome) were captured using Agilent SureSelect Target Capture Kit V2.0, and sequenced at 100-bp paired-end. The single nucleotide variants (SNVs) and small insertions and deletions (INDELs) were called using The Genome Analysis Toolkit (GATK), and the exon level copy number variants (CNVs) we identified using patternCNV. The whole-genome mate-pair libraries of both normal and tumor DNAs with 3kb insert sizes were sequenced paired end at 50-bp. The large SVs of CNVs, large INDELs, translocations, and inversions were identified using the SnowShoes-SV algorithm. The RNA sequencing libraries of 8 FL tumors were constructed using Illumina TruSeq protocol, and sequenced at 50-bp paired end. The RNA-Seq data were analyzed using TopHat and the fusion transcripts were identified using SnowShoes-FTD.

Our analysis of SNVs and INDELs revealed mutations in previously reported genes including MLL2, CREBBP, TNFRSF14, and histone cluster genes (HIST1H2AM, HIST1H2BD). In addition, we identified novel recurrent mutations in cysteine-rich PAK1 inhibitor (CRIPAK) in 25% of the tumors. In a secondary analysis performed by Sanger sequencing or re-analysis of publically available RNA sequencing data, we identified CRIPAK mutations in 44% of FL (n=32) and 28% of DLBCL tumors (n=102). Bioinformatics analysis shows that the coding region of CRIPAK is highly enriched with the protein functional domain, post-SET, which is usually found in histone lysine methyltransferases (HMTase) genes including MLL2 and EZH2 that are known to be important in lymphomagenesis. Interestingly, CRIPAK is part of the same regulatory network consisted of previously identified lymphoma genes including MLL2, EZH2, CREBBP, and EP300, according to the shortest path algorithm by MetaCore (Philadelphia, Pennsylvania). Recurrent SVs identified in the FL tumors included the well-known IGH-BCL2 translocation, or t(14;18), in 6 out of 8 cases (75%) and the chr1q amplifications in 4 out of 8 (50%) tumors. Other non-recurrent large CNVs involving entire chromosomes or chromosome arms, as well as other inter- and intra-chromosomal structural variants were detected in individual tumors. In addition, we identified and validated 6 fusion transcripts from the transcriptome sequencing data in 3 out of 8 cases (38%).

While our sample size is small, we found that SNVs and INDELs in MLL2, CREBBP, TNFRSF14, CRIPAK, and histone cluster genes, as well as t(14;18), did not distinguish indolent or aggressive tumors. However, all aggressive (4/4, 100%) and none of the indolent tumors had gains in chr1q; and the presence of RNA fusion transcripts were observed in aggressive tumors only (3/4, 75%). Additionally, we found that aggressive tumors had higher numbers of genes with point mutations (SNVs and short INDELs) (40 ± 7.6 vs. 26 ± 2.6; aggressive vs. indolent), higher numbers of genes impacted by copy number aberrations (1060 ± 263.7 vs. 233 ± 133.9), and higher numbers of large SVs (24 ± 10 vs. 6 ± 1.6). Taken together, our comprehensive analysis of 8 FL tumors reveals genetic diversity among newly diagnosed FL patients, identifies novel and recurrent mutations in CRIPAK, and finds that high tumor complexity and DNA instability may be indicators of aggressive disease.