Abstract

Clonal evolution is considered as a hallmark of progression in chronic lymphocytic leukemia (CLL). Next-generation sequencing technologies have expanded our knowledge of genetic abnormalities in CLL and enabled to describe marked clonal changes. The acquisition of driver mutations accompanied by selectively neutral passenger changes may be essential to understand the transformation from diagnosis to later more aggressive stages. However, the role of genetic mutations and clonal evolution during the clinical progression prior any therapy is still largely unknown. Longitudinal studies analyzing CLL patients repeatedly before intervening treatment are currently scarce.

Patients and methods: We examined the exomes from 35 CLL patients in 2 time-points. Two groups of patients were characterized: (i)patients with progression (n=26) in which we analyzed samples taken from an early stable stage (inactive disease) and during clinical progression (active disease), but before treatment (median of time to first treatment=2.7 years); (ii)patients without progression with a stable inactive disease until last follow-up (n=9) (median follow-up=5.25 years). We also compared patients that gained new cytogenetic aberration detected by FISH in the 2nd time-point with those who did not.

Sequencing libraries were prepared using TruSeq Exome Enrichment and sequenced by Illumina HiSeq1000 (84X). Somatic mutation calling was performed by a standardized bioinformatics pipeline. Thereafter, driver mutations were identified using the Cancer Genome Interpreter (https://www.cancergenomeinterpreter.org), a novel tool that identifies variants that are already validated as oncogenic and predicts the effect of the mutations of unknown significance.

Results: We identified 397 somatic mutations in 364 different genes, ranging from 4 to 26 mutations per patient. Among them, 58 driver mutations were identified, being SF3B1 (6/35, 17.1%), TP53 (4/35, 11.4%) and NOTCH1 (4/35, 11.4%) the most common mutated genes. Comparing progressive vs. stable group, CLL patients with clinical progression showed a higher intra-tumoral heterogeneity than cases without progression (median of somatic mutations=14[4-26] vs. 9[5-14]).

Comparing both tumoral time-points in the same patient, we identified a total of 11 acquired driver mutations and 7 mutations increasing its allele frequency in more than double in the 2nd time-point respect to the 1st one. All of them were detected in patients with clinical progression. Interestingly, TP53 and BIRC3 exhibited recurrently acquired mutations (detected each one in 2 cases). Three driver mutations in cancer genes not yet known for CLL (DHX9, GNAQ and HDAC2) were also acquired. Within CLL progressive patients (n=26), we observed clonal evolution characterized by acquired cytogenetic aberration in 9 cases. In patients with progression but no cytogenetic aberration gained at the 2nd moment (n=17), we detected that almost half of them (7/17) showed clonal evolution by acquired or doubled driver mutations. In the remaining patients with clinical progression but without any clonal evolution (n=10), 6 cases showed a driver mutation of CLL genes associated with bad prognosis (SF3B1, TP53, NOTCH1 or RPS15) already at first time-point.

In the stable group (n=9), none acquired or doubled mutation was detected. However, clonal evolution characterized by acquired cytogenetic aberration was observed in 4/9 stable patients: two of them acquired 13q- whereas the other two acquired 11q-. Within stable patients without clonal evolution (n=5), we detected one case with a driver mutation in SF3B1 already at 1st time-point (follow-up=5 years).

Conclusion: Clonal evolution represents a central feature of tumor progression in CLL. Our data show that the disease is evolving during time even in stable patients without any clinical signs of disease activity. In progressive patients, the disease evolution is accompanied by new appearance or accumulation of driver mutations and cytogenetic aberrations. Moreover, progressive patients that showed less or no changes during time bore typical CLL drivers at the first time-point.

Funding: Seventh Framework Programme (NGS-PTL/2012-2015/no.306242); Ministry of Education, Youth and Sports (2013-2015, no.7E13008; CEITEC 2020 (LQ1601)); AZV-MZ-CR 15-31834A-4/2015 and TACR (TEO2000058/2014-2019); PI15/01471; Junta de Castilla y León (MHS).

Disclosures

No relevant conflicts of interest to declare.

Author notes

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Asterisk with author names denotes non-ASH members.