A Quantitative Analysis of Subclonal and Clonal Gene Mutations before and after Therapy in Chronic Lymphocytic Leukemia

Abstract

Purpose: Chronic lymphocytic leukemia (CLL)-associated gene mutations that influence CLL cell fitness and chemotherapy resistance should increase in clonal representation when measured before therapy and at relapse.Experimental Design: To uncover mutations associated with CLL relapse, we have performed whole-exome sequencing in a discovery cohort of 61 relapsed CLL patients identifying 86 recurrently mutated genes. The variant allele fractions (VAF) of 19 genes with mutations in !3 of 61 cases were measured in 53 paired pre-and posttreatment CLL samples sorted to purity using panel-based deep resequencing or by droplet digital PCR.Results: We identify mutations in TP53 as the dominant subclonal gene driver of relapsed CLL often demonstrating substantial increases in VAFs. Subclonal mutations in SAMHD1 also recurrently demonstrated increased VAFs at relapse. Mutations in ATP10A, FAT3, FAM50A, and MGA, although infrequent, demonstrated enrichment in !2 cases each. In contrast, mutations in NOTCH1, SF3B1, POT1, FBXW7, MYD88, NXF1, XPO1, ZMYM3, or CHD2 were predominantly already clonal prior to therapy indicative of a pretreatment pathogenetic driver role in CLL. Quantitative analyses of clonal dynamics uncover rising, stable, and falling clones and subclones without clear evidence that gene mutations other than in TP53 and possibly SAMHD1 are frequently selected for at CLL relapse.Conclusions: Data in aggregate support a provisional categorization of CLL-associated recurrently mutated genes into three classes (i) often subclonal before therapy and strongly enriched after therapy, or, (ii) mostly clonal before therapy or without further enrichments at relapse, or, (iii) subclonal before and after therapy and enriching only in sporadic cases.

Cell-Intrinsic Determinants of Ibrutinib-Induced Apoptosis in Chronic Lymphocytic Leukemia

“…The CLL cases selected for this study were highly characterized for known clinically relevant traits. In addition, the relapsed CLL samples were analyzed for gene mutations through whole exome sequencing (WES) and subsequent Sanger sequencing of all recurrently mutated genes as detected through WES, SNP 6.0 profiling of genomic copy number changes and deep panel-based gene re-sequencing of TP53, NOTCH1 and other genes as described(28). …”

“…Solution-based exome capture and HiSeq2000-based massively parallel sequencing and bioinformatic pipeline analysis of WES data was performed as described(28). …”

Chronic lymphocytic leukaemia genomics and the precision medicine era

“…It was shown that 3-5% of CLL patients have acquired mutations in SAMHD1 at diagnosis (Clifford et al, 2014). However, SAMHD1 mutation frequency is increased in relapsed/refractory CLL (9-11%) without associated increase of other poor risk factors, such as 11q deletion or unmutated IGHV (Clifford et al, 2014;Amin et al, 2016). Two independent studies associated SAMHD1 mutations with resistance to standard CLL therapies (Clifford et al, 2014;Amin et al, 2016).…”

“…However, SAMHD1 mutation frequency is increased in relapsed/refractory CLL (9-11%) without associated increase of other poor risk factors, such as 11q deletion or unmutated IGHV (Clifford et al, 2014;Amin et al, 2016). Two independent studies associated SAMHD1 mutations with resistance to standard CLL therapies (Clifford et al, 2014;Amin et al, 2016). Indeed, standard treatments may select pre-existing clones carrying SAMHD1 mutations (Amin et al, 2016).…”

Routine sequencing in CLL has prognostic implications and provides new insight into pathogenesis and targeted treatments

“…Whole‐exome sequencing (WES) has led to the discovery of mutations in genes such as SF3B1 , which encodes a protein that normally acts as part of the RNA spliceosome and mRNA processing machinery, with a reported mutational frequency in CLL between 10–15% (Wang et al , ; Wan & Wu, ). While functional loss or gain within the mutation is currently unclear, SF3B1 mutations cause deleterious effects on DNA damage repair and are associated with a shorter time‐to‐first treatment (TTFT) and overall survival (OS) (Jeromin et al , ; Te Raa et al , ; Amin et al , ; Nadeu et al , ). Additional examples include mutations in TP53, BIRC3, ATM, KRAS, POT1 and NOTCH1, which were all associated with reduced responses to treatment and shorter survival (Rossi et al , ; Cortese et al , ; Landau et al , ; Herling et al , ; Nadeu et al , ).…”