Large-Scale CLL Genome Analysis Reveals Novel Cancer Genes, Including SF3B1

Abstract 463

The somatic genetic basis of chronic lymphocytic leukemia (CLL), a common and clinically heterogenous adult leukemia, remains poorly understood. Massively parallel sequencing technology provides a method for systematic discovery of genetic alterations that underlie disease, and for uncovering new therapeutic targets and biomarkers. We therefore performed DNA sequencing of 91 CLL samples with matched germline, consisting of 88 exomes and 3 genomes. Samples were collected from patients displaying a range of characteristics representing the broad clinical spectrum of CLL. Libraries were constructed and sequenced on an Illumina GA-II sequencer to deep coverage. Point mutations and indels were detected by comparing sequences of each tumor to its corresponding normal.

We detected 1828 non-silent mutations in protein-coding sequences, corresponding to an average somatic mutation rate of 0.72/Mb (range 0.075–2.14). Nine cancer genes were identified, as they were mutated significantly more often than the background rate given their sequence composition across all 91 CLL/normal pairs. Four have been previously described in CLL (TP53, ATM, MYD88 and NOTCH1); the others were novel (SF3B1, ZMYM3, MAPK1, FBXW7 and DDX3X). Strikingly, SF3B1, which functions at the catalytic core of the spliceosome, was mutated the second most frequently (15%). All 14 identified mutations localized to a discrete region (exons 12–18), and 7 were recurrent (K700E). We additionally validated the SF3B1-K700E mutation through genotyping of 101 independent CLL samples. The 9 significantly mutated genes fell into 5 core signaling pathways, in which the genes play established roles: DNA damage repair and cell-cycle control (TP53, ATM), Notch signaling (FBXW7, NOTCH1), inflammatory pathways (MYD88, DDX3X, MAPK1) and RNA splicing/processing (SF3B1, DDX3X).

The common cytogenetic aberrations in CLL carry strong prognostic significance, implying that they reflect distinct pathogenesis. Supporting this hypothesis, we discovered strong associations between different driver mutations and key FISH abnormalities. Most TP53 mutations were in samples with del(17p) (p<0.001), resulting in homozygous p53 inactivation. Del(11q) was marginally associated with mutation in ATM which lies in the minimally deleted region of chr. 11q (p=0.09); but clearly associated with SF3B1 mutation (p=0.004), suggesting interaction within this clinical subgroup of CLL. NOTCH1 and FBXW7 mutations (present in independent samples) were associated with trisomy 12 (p=0.009 and 0.05), suggesting that aberrant Notch signaling plays an important role in this clinical subgroup. Finally, all detected mutations in MYD88 (known to be activating for the NFkB pathway) were present in samples harboring heterozygous del(13q) (p=0.009) with mutated IGHV status (p=0.002). These findings suggest that NFkB activation plays a driving role in this low risk clinical subgroup.

To define the impact of the mutated cancer genes on disease outcome, we constructed a Cox multivariable regression model for factors contributing to earlier time to first therapy (TTFT) in the 91 CLLs. SF3B1 mutation was predictive of poor prognosis (HR 3.17, p=0.004), independent of other established markers (i.e. IGVH mutation; del(17p); ATM mutation). Consistent with this analysis, patients harboring the SF3B1 mutation alone had short TTFT, as did patients with del(11q) or del(11q)+SF3B1 mutation. All 3 groups demonstrated significantly shorter TTFT than patients without either SF3B1 mutation or del(11q). Because SF3B1 encodes a splicing factor, we looked for functional evidence of splicing alterations associated with SF3B1 mutation. Indeed, mRNA targets of the spliceosome exhibited greater intron retention in CLLs with mutated vs nonmutated SF3B1, confirming alteration in normal SF3B1 function.

Understanding the mutational landscape of CLL provides a starting point for systematic analyses to address fundamental questions in CLL, including how mutated genes alter cellular networks and phenotypes, and thereby contribute to disease heterogeneity. Our discovery of striking associations between driver mutations and standard CLL prognostic markers (cytogenetic aberrations, IGVH mutational status) suggest synergistic interactions. In particular, our studies highlight pre-mRNA splicing as a critical but thus far unexplored cellular process contributing to CLL.