Impact of Infrequently Mutated Genes on Prognosis in 531 Untreated CLL Patients

Background: In a previous multicentre study, 55 recurrent aberrations were identified in 538 chronic lymphocytic leukemia (CLL) cases including 278 pre-treatment samples (Landau et al., Nature 2015). Some of these aberrations are frequent and their impact on prognosis in CLL is well analyzed. However limited data exist on the rarely mutated genes.

Aim: Characterize 531 untreated CLL patients in terms of infrequently mutated genes and impact on prognosis.

Patients and Methods: 531 CLL patients at diagnosis or without prior treatment were screened for gene mutations by a targeted amplicon sequencing approach: ASXL1, ATM, BIRC3, BRAF, BTK, EGR2, FBXW7, KRAS, MAP2K1, MYD88, NRAS, NFKBIE, NOTCH1, PLCG2, POT1, SAMHD1, SF3B1, SRSF2, TP53, U2AF1, XPO1, and ZRSR2 . The mean overall read depth for all genes was 2,496 (range: 305-13,078). IGHV mutational status was analyzed in all cases. IGHV unmutated status (IGHV-U) was defined by sequence identity ≥98%. Chromosome banding analysis and interphase FISH with probes for 17p13, 13q14, 11q22 and centromeric region of chromosome 12 were performed in all cases. Male:female ratio was 1.6:1 and median age was 66 years (range: 30 - 87 years). In all cases data on time to first treatment (TTT) and overall survival (OS) was available with a median follow-up of 6 years, each.

Results: Overall 223 (42%) mutated cases comprising 343 mutations were detected in 19/22 analyzed genes. The frequencies of the gene mutations were as follows: NOTCH1 (12%), ATM (9%), SF3B1 (9%), TP53 (7%), NFKBIE (5%), XPO1 (4%), BIRC3 (3%), MYD88 (2%), POT1 (2%), EGR2 (2%), FBXW7 (2%), KRAS (2%), BRAF (1%), NRAS (1%), ASXL1 (<1%), MAP2K1 (<1%), SAMHD1 (<1%), U2AF1 (<1%), and ZRSR2 (<1%). No mutations were detected in SRSF2 and, as expected in untreated CLL cases, also not in BTK and PLCG2 .

We restricted the statistical analyses on infrequently mutated genes (≤5%) found in at least 10 mutated cases. Most of the gene mutations were associated with IGHV-U: NFKBIE (10% vs. 2%, p<0.001), POT1 (6% vs. 1%, p<0.001), EGR2 (4% vs. 1%, p=0.005), and XPO1 (11% vs. 1%, p<0.001). MYD88 was found only in IGHV-M (3% vs. 0%, p=0.017) and was associated with del(13q) sole (3% vs. 1%, p=0.049). NOTCH1 mutated vs. wild-type (wt) cases showed significantly higher frequencies of mutations in NFKBIE (11% vs. 4%, p=0.029), XPO1 (12% vs. 3%, p=0.004) and KRAS (8% vs. 1%, p=0.002). Accordingly, following genes were highly mutated in cases with trisomy 12 cases vs. without: NFKBIE (10% vs. 4%, p=0.037), KRAS (9% vs. 1%, p<0.001), BIRC3 (10% vs. 2%, p=0.003), and FBXW7 (10% vs. 1%, p<0.001). In contrast, most of the mutations were rare in patients with del(13q) sole: NFKBIE (2% vs. 7%, p=0.008), FBXW7 (0% vs. 4%, p=0.014), and KRAS (0% vs. 3%, p=0.005). Interestingly, EGR2 mutations were associated with del(11q) (7% vs. 1%, p=0.016), XPO1 with ATM (13% vs. 4%, p=0.011) and NFKBIE mutations (15% vs. 4%, p=0.021), and BIRC3 with FBXW7 mutations (18% vs. 3%, p=0.045).

In Kaplan-Meier analyses, the infrequently mutated genes NFKBIE (4 vs. 8 years, p=0.006), POT1 (3 vs. 8 years, p=0.012), EGR2 (1 vs. 8 years, p=0.020), and XPO1 (3 vs. 8 years, p<0.001) showed significant shorter TTT vs. wt cases, but no effect on OS. Whereas BIRC3 showed only impact on OS (5 year-OS: 61% vs. 88%, p=0.002). Cox regression analysis was performed with following covariates: genes with at least 2% mutation frequency, IGHV status, FISH and cytogenetic aberrations. In multivariate analysis for TTT following markers showed significant effect: IGHV-M (RR=relative risk: 0.3, p<0.001), del(11q) (RR: 2.1, p=0.001), trisomy 12 (RR: 2.1, p<0.001) and SF3B1 mutation (RR: 1.9; p=0.001). The rarely mutated genes NFKBIE, POT1, EGR2 and XPO1 that were significant in univariate analysis showed no independent impact. For OS BIRC3 (RR: 4.1, p<0.001) besides IGHV-M (RR: 0.6, p=0.031) and del(17p) (RR: 5.3, P=0.002) retained significant effect. None of the other rarely mutated genes showed statistical significance already in univariate analysis.

Conclusion: In 42% of 531 untreated CLL patients, mutations can be found in 19 distinct genes. Patients with the rarely mutated genes NFKBIE, POT1, EGR2 and XPO1 show reduced time to treatment, whereas BIRC3 mutations are associated independently with shorter overall survival. Even though most of the rare gene mutations analyzed here have no strong impact on prognosis, some of them might be interesting for targeted therapy approaches in the near future.