Whole-Genome Analysis of Adult T-Cell Leukemia/Lymphoma

Adult T-cell leukemia/lymphoma (ATL) is an aggressive T-cell malignancy with a dismal prognosis, caused by HTLV-1. Although our previous study, mainly using whole-exome sequencing and SNP array karyotyping, discovered many driver mutations and copy number alterations (CNAs), the whole-genome landscape of ATL still remains elusive.

To this end, we have performed high-depth whole-genome sequencing (WGS) of 155 ATL cases with a median sequencing depth of 96-fold for tumors. Among them, 75 cases were also analyzed by RNA sequencing (RNA-seq). In total, we detected 1,952,490 single nucleotide variants (SNVs) and 159,141 insertion-deletions (4.0 SNVs and 0.3 indels/Mb/case), 10,279 SVs (66.3 SVs/case), and 3,975 CN altered segments (25.7 segments/case). Using several driver discovery algorithms (dNdScv, MutSig2CV, and DriverPower), we identified 47 significantly mutated genes, 19 of which were mutated in more than 10% of cases. These included several novel mutations, such as those affecting XPO1 (7.1%), ZNF292 (6.5%), and ITGB1 (5.2%). Using GISTIC2.0, we identified 13 significant CNAs, such as IRF4 amplifications and CDKN2A deletions, consistent with previous SNP array data. To detect significantly recurrent SVs, we calculated SV breakpoint frequency and identified 13 genes affected by SVs, including the previously identified genes (such as CARD11, CD274, and TP73). In addition, we investigated recurrent mutations in non-coding elements by DriverPower and LARVA and discovered 12 recurrently mutated elements. Among them, the most frequent were splice site mutations, including those of HLA-A and HLA-B, most of which caused loss of function as revealed by RNA-seq. By contrast, we found recurrent mutations in TP73 splice site, which induced skipping of exons 2 and 3, generating a dominant-negative variant similar to their SVs. In addition, recurrent non-coding elements contained several novel regions, such as 3´-untranslated region (UTR) of NFKBIZ and 5´- UTR of TMSB4X.

Altogether, a total of 56 genes were recurrently altered. The median number of driver alterations was eight per case, and at least one driver alteration was found in 149 cases (96.1%). Among 56 driver genes, 40 (71.4%) genes were affected by more than one alteration class. Some drivers, such as CDKN2A, IKZF2, and CD274, were affected almost exclusively by CNAs and/or SVs, while showing quite high alteration frequencies (11.6-29.0%). These observations suggest that WGS presented a substantially different overview of driver alterations from our previous study. The overall numbers of mutations and SVs were linked to these driver alterations, suggesting their etiology. In particular, inactivation of EP300 and immune-related molecules, such as HLA-A, HLA-B, and CD58, were associated with an increased number of mutations and SVs, especially deletions and tandem duplications. By contrast, cases with TP53-altered cases harbored more inversions and translocations. These results emphasize a pivotal role of immune evasion for acquiring genetic alterations to drive ATL progression.

To define molecular subgroups in ATL, we integrated the 56 identified genetic drivers using non-negative matrix factorization clustering and identified two robust subgroups with discrete clinical and genetic characteristics. Group 1 was enriched with alterations affecting distal components of T-cell receptor (TCR)/NF-κB signaling (such as CARD11, PRKCB, and IRF4) and immune-related molecules (HLA-A, HLA-B, and CD58), whereas proximal regulators of TCR/NF-κB signaling (PLCG1, VAV1, and CD28) and a JAK/STAT signaling molecule (STAT3) were more frequently altered in group 2. In addition, group 1 cases had a larger number of mutations, SVs, and CNAs than group 2 cases. Clinically, most cases with lymphoma subtype were classified into group 1, whereas group 2 mainly consisted of cases with leukemic subtypes. Moreover, group1 cases showed a worse overall survival than group 2, independently of clinical subtype. These results suggest the biological and clinical relevance of the molecular classification of ATL.

In summary, our WGS analysis not only identifies novel somatic alterations but also extends the overview of ATL genome. We also propose a new molecular classification of ATL, with its clinical relevance, which can lead to the future improvement of patient management.