ALBERT

Description: Genomic studies have recently identified RPS15 as a new driver gene in aggressive and chemorefractory cases of chronic lymphocytic leukemia (CLL). RPS15 encodes a ribosomal protein whose conserved C-terminal domain extends into the decoding center of the ribosome. We demonstrate that mutations in highly conserved residues of this domain affect protein stability, by increasing its ubiquitin-mediated degradation, and cell-proliferation rates. On the other hand, we show that mutated RPS15 can be loaded into the ribosomes, directly impacting on global protein synthesis and/or translational fidelity in a mutation-specific manner. Quantitative mass spectrometry analyses suggest that RPS15 variants may induce additional alterations in the translational machinery, as well as a metabolic shift at the proteome level in HEK293T and MEC-1 cells. These results indicate that CLL-related RPS15 mutations might act following patterns known for other ribosomal diseases, likely switching from a hypo- to a hyperproliferative phenotype driven by mutated ribosomes. In this scenario, loss of translational fidelity causing altered cell proteostasis can be proposed as a new molecular mechanism involved in CLL pathobiology.

Description: Genomic studies have provided a complete profile of somatic mutations in chronic lymphocytic leukemia (CLL). These comprehensive approaches have revealed a relatively large number of mutated genes, the adverse prognostic value of some of which has been demonstrated in a number of reports. Recent studies have shown the clinical relevance of TP53 mutations at very low allele frequency. The presence and prognostic impact of minor mutated clones of other CLL driver genes and their clonal dynamics in the evolution of the disease is not well known. The goal of this study was to explore the presence of clonal and subclonal mutations of TP53, SF3B1, BIRC3, and ATM using an ultra-deep next-generation sequencing (NGS) strategy, to define the evolution of these subclones in different time-points of the disease, and to determine their influence in the outcome of the patients. Samples from 363 untreated CLL cases were included in this study. Copy number alterations were investigated by high density SNP-arrays or by quantitative PCR in 341 and 16 cases, respectively. Targeted ultra-deep NGS of TP53 (exons 4-10), ATM (exons 2-63), BIRC3 (exons 2-9), and SF3B1 (exons 14-16 and 18), including splicing sites, was performed using the Access-Array system (Fluidigm) and sequenced in a MiSeq equipment (Illumina). This methodology combined with a robust bioinformatic analysis based on well-known available tools allowed the identification of mutations down to 0.3% of variant allele frequency (VAF). Results obtained were fully verified by orthogonal techniques. Twelve per cent of VAF was used as threshold for the classification of clonal or subclonal mutations since 12% was the cut-off for detection of mutations by Sanger sequencing. Deletions of 11q comprising ATM or BIRC3 were found in 7% of the cases and were associated with mutations of the other ATM allele in 19/26 (73%) cases and BIRC3 in 3/23 (13%). Deletions of 17p were found in 19 (5%) cases and co-existed with TP53 mutations in 15 (79%) of them. Regarding the mutational status of the studied genes, TP53 mutations were present in 11.6% of patients (7.2% clonal, 4.4% subclonal), ATM mutations in 10% (7% clonal, 1% subclonal, 2% germline mutations considered pathogenic), SF3B1 mutations in 12% (7% clonal, 5% subclonal), and BIRC3 mutations in 4% (2% clonal, 2% subclonal). These subclonal mutations had similar molecular characteristics to their respective high-allele frequency mutations supporting a comparable pathogenic effect. In this regard, clonal and subclonal SF3B1 mutations were associated with shorter time to first treatment (TTT) independently of IGHV mutations. Clonal and subclonal TP53 mutations predicted for shorter overall survival (OS) together with the IGHV mutational status, although the impact of isolated TP53 mutations (i.e. without 17p deletion) on OS was not so evident, as has been the case in other studies. In addition, the outcome of patients with clonal and subclonal BIRC3 mutations showed a similar significant shorter OS. Regarding ATM, the effect of isolated subclonal ATM mutations could not be evaluated because of their low number, but ATM mutations as a whole had a significant impact on TTT even in the absence of 11q deletions. This study also reinforces the need to study the germline of the patients to fully characterize the ATM mutations observed in the tumors. Of note, germline variants previously described as pathogenic were associated with 11q deletions, confirming the hypothesis already suggested that these germline variants may influence disease progression through loss of the otherallele. Clonal dynamics was examined in longitudinal samples of 45 CLL patients. We confirmed the expansion of most TP53 mutated clones after therapy. However, both TP53 and SF3B1 mutations expanded also before any therapy in some patients, indicating that progressive dynamics of these clones is not only dependent on therapy selection. On the contrary, small ATM mutated clones seemed to be more stable. Although the number of cases is limited, we observed that clonal evolution in longitudinal samples had an unfavorable impact on OS. In conclusion, this study shows the presence of a high number of subclonal mutations of different driver genes in CLL and provides insights on the impact of these mutations on the outcome of the patients. These findings suggest that the characterization of the subclonal architecture may be relevant for a better management of CLL patients. Disclosures No relevant conflicts of interest to declare.

Description: Introduction: DLBCL is biological and clinically highly heterogeneous. Although different genetic aberrations, including recurrent somatic mutations, have been described in this tumor, their clinical impact remains to be clarified. The aim of the present study was to determine somatic mutations and copy number alterations of a selected group of genes in patients with DLBCL, in order to assess their prognostic importance and to identify potential personalized targeted drugs for these patients. Methods: 150 patients (78M/72F; median age, 66 years) diagnosed with de novo DLBCL no otherwise specified at Hospital Clínic and other institutions of the GELCAB, treated with immunochemotherapy, were included in the study. An independent series of 111 patients (54M/57F; median age, 63 years), diagnosed at different Japanese and Spanish institutions, was used to validate the significant findings. Targeted next generation sequencing (NGS) of 106 representative genes related with DLBCL and Copy Number Alterations (CNA) assessment were performed. Ten functional pathways were pre-defined, including NOTCH, tumor suppressor genes, JAK/STAT, epigenome/chromatic modifier, BCR signaling, PI3K-AKT-mTOR, MAP-kinase, B-cell differentiation, immune surveillance and cell cycle alterations. Cell of origin (COO) of the tumors was established using gene expression or the Lymph2Cx assay. Genomic-guided potential therapeutic opportunities for each patient were identified in silico by a Cancer Genome Interpreter platform. Results: A total of 765 potential driver mutations were identified in 89 of the 106 genes with a slightly higher number in germinal center B-cell like (GCB) than activated B-cell-like (ABC) DLBCL subtype. The most frequently mutated genes found in 〉15% of the cases were KMT2D (MLL2), MYD88, CREBBP and TP53, with other 27 genes being mutated in 〉5% of the cases. Several genes were differentially mutated in GCB DLBCL subtype (KMT2D, CREBBP, TNFRSF14, B2M, EZH2, GNA13, FOXO1, ACTB and SOCS1) or ABC subtype (MYD88, PIM1, CD79B and PRDM1). No relevant differences were observed in the clinical features according to individual mutations or CNA. No single gene mutation predicted response to therapy. Genetic alterations in KLHL6, ETV6, SGK1, L8q12.1, CD79B, PIM1 and TP53 predicted poor OS, whereas mutations of SOCS1 were associated with better outcome. Alterations in NOTCH pathway and tumor suppressor pathway were associated with poor outcome, whereas those of JAK/STAT pathway showed favorable prognosis (see table for detailed data). NOTCH pathway (HR 2.8; p=0.006) and tumor suppressor pathway (HR 2.4; p=0.005) maintained independent significance for OS along with R-IPI (H 4.0; p=0.006) in a multivariate analysis that also included COO and beta2-microglobulin. In addition, the prognostic value of NOTCH and tumor suppressor pathways was confirmed in the independent validation series. Finally, we identified 69 cases (46%) carrying at least one genomic alteration in 9 genes considered a biomarker of drug response supported by data of early clinical trials or pre-clinical assays; tumors of additional 26 patients (17%) had at least one gene alteration that could be exploited by a drug repurposing strategy. Conclusions: Integrating the deep sequencing analysis of a panel of selected genes and CNA, we have recognized novel target genes and defined the clinical relevance of alterations of NOTCH and tumor suppressor pathways in DLBCL. Using an in silico prescription pipeline we have also identified a number of candidate drugs with potential therapeutic interactions with driver oncogenic proteins. All these findings may orient future preclinical and clinical intervention strategies in DLBCL. Table Initial features, response to therapy and outcome according to pathways´ status Table. Initial features, response to therapy and outcome according to pathways´ status Disclosures Sancho: Celltrion, Inc: Research Funding; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Gonzalez Barca:Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Roche: Speakers Bureau; Gilead: Speakers Bureau. Ohshima:Kyowa Hakko Kirin Co., Ltd.: Research Funding, Speakers Bureau; CHUGAI PHARMACEUTICAL CO.,LTD.: Research Funding, Speakers Bureau. Akashi:Sunitomo Dainippon Pharma: Consultancy; Celgene: Research Funding; Kyowa Hakko Kirin: Consultancy, Research Funding; Bristol Meyers Squibb: Research Funding; Asahi Kasei Pharma Corporation: Research Funding; Chugai Pharmaceutical Co., Ltd.: Research Funding; Shionogi & Co., Ltd: Research Funding; Astellas Pharma: Research Funding.

Description: Introduction: Mature normal and tumor B cells express a unique rearranged immunoglobulin (IG) gene that can be used as a marker of the clonal expansion of the cell. Somatic hypermutation (SHM) in the V(D)J region of IG genes are acquired in the germinal center and are a surrogate imprint of the cell of origin of lymphoid neoplasms. In chronic lymphocytic leukemia (CLL) and mantle cell lymphoma (MCL), the identification of SHM distinguishes subtypes of tumors with different clinical and biological behavior. Although still less studied, cases carrying highly similar IG sequences (i.e. stereotyped IG), specific light chain (LC) rearrangements, and the presence of class switch recombination (CSR) of the constant region of the heavy chains further sub-classify patients into potentially distinct clinico-biological subgroups. The analysis of the rearranged IG gene is currently performed by specific Sanger sequencing (SSeq) or next-generation sequencing protocols. Whole-genome sequencing (WGS) of B-cell neoplasms should store the information to reconstruct the entire rearranged IG gene [heavy (IGH) and kappa or lambda (IGK, IGL) LC]. However, the high genomic complexity and homology of these regions have prevented the analysis of the rearranged IG genes in WGS using standard bioinformatics pipelines. Aim: To assess the use of WGS data to fully characterize the rearranged IG gene in B-cell neoplasms. Methods: We developed IgCaller, a fast, easy-to-run program that uses already aligned WGS data to dissect the rearranged IGH V(D)J genes, IGK and IGL VJ genes, and the presence of constant heavy chain CSR. IgCaller also determines the homology of the rearranged sequences compared to the patient's germ line or reference genome. We demonstrated the accuracy of IgCaller using WGS data of 331 B-cell neoplasms [240 CLL (152 cohort 1 (C1)-CLL; 88 independent cohort 2 (C2)-CLL), 61 MCL, and 30 multiple myeloma (MM)] and compared with SSeq of the IGH V(D)J and/or LC and isotype expression. Results: IgCaller identified a complete IGH productive rearrangement [V(D)J] in 133 (88%) C1-CLL, 80 (91%) C2-CLL, 61 (100%) MCL, and 21 (70%) MM. A partial (VJ) rearrangement was detected in 8 (5%) C1-CLL and 1 (3%) MM. Available SSeq of the V(D)J or at least V gene for 131 C1-CLL, 10 C2-CLL, and 60 MCL successfully characterized by WGS highlighted only one discordant V(D)J rearrangement. Small discrepancies (only J or V disagreement) were found when the J (n=4) or V (n=1) gene identified by SSeq based on homology (IMGT/V-QUEST tool) did not correspond to the rearranged gene detected by WGS, which was the second scoring gene in IMGT/V-QUEST suggesting that our non-homology WGS-based approach might be more accurate. Of note, IgCaller identified the presence of two distinct IGH subclones in 1 case. Next, the comparison of the percentage of homology of the rearranged sequence to the germ line in 131 C1-CLL and 60 MCL with complete V gene both by SSeq and WGS showed a high correlation and concordance in both cohorts [R〉0.95, p90% B-cell neoplasms studied. The complete characterization of the rearranged IG gene based on WGS data, when available, could facilitate the analysis of LC rearrangements and CSR, and replace the traditional SSeq of the IG loci both in research and clinical settings. Disclosures No relevant conflicts of interest to declare.

Description: Background: DNA methylation has been extensively described to be related with gene regulation. However, recent data indicate that DNA methylation changes in repressed regions accumulate in every cell division, and thus, they can reflect the proliferative history of the cell. The evaluation of this epigenetic feature in cancer cells may provide information regarding the tumor cell biological evolution and may assist to predict the outcome of the patients. Aims: The global aim of this study was to develop a DNA methylation-based proliferative history score and determine its possible prognostic value in chronic lymphocytic leukemia (CLL). Methods: We used 450k methylation arrays from normal B cells subpopulations and CLLs at diagnosis. To analyze DNA methylation changes specifically in leukemic cells, we performed stringent data quality checks and corrections including FACS sorting and in silico purification of DNA methylation. Thus, we retained 67 normal B cells and 477 CLLs, comprising 140 naive-like CLLs (nCLL), 106 intermediate CLLs (iCLL) and 231 memory-like CLLs (mCLL) based on a recent epigenetic classification of cellular origin. We mapped CpGs falling in repressive regions using ChIP-Seq data of 6 histone marks from healthy B cell subpopulations and CLL patients. With the methylation levels of CpGs in repressive chromatin, we built one score per each sample which we termed Epigenetic Mitotic History (epiMH, ranging from 0 to 1). The epiMH was integrated with whole genome sequencing (WGS) and microarray expression data of the very same CLL patients (n=126). Finally, we analyzed whether epiMH was related to clinical behavior. Results: We showed that epiMH is widely variable in normal B cells, with more advanced differentiation stages displaying the highest epiMH, presumably due to their greater accumulated proliferative history. Then, we calculated the epiMH in CLLs with different cellular origins, namely, nCLL, iCLL and mCLL, and we correlated it with different biological features. Using mutational signatures from WGS data of the same samples, we identified significant correlations of epiMH with signatures 1, 5 and 9, that have been reported to various cell division related mutational processes. Next, differential gene expression analysis between CLLs with high epiMH as compared to those with low epiMH revealed an enrichment in gene signatures related to active proliferation. Collectively, these results support the concept that the epiMH may reflect the past and present proliferative history of the cell. Finally, we postulated that the epiMH may be related with future proliferative capacity and clinical behavior. To test this, we analyzed the clinical impact of epiMH in patients from each epigenetic subgroup. An univariate analysis with epiMH as quantitative variable revealed that the higher the epiMH the worse clinical behavior. Additionally, we performed a multivariate Cox regression model for both overall survival (OS) and time to first treatment (TTT) including epiMH together with other well established prognostic factors for CLL, including age, epigenetic subgroups and the number of driver alterations. We showed that epiMH was an independent significant variable for both OS (HR=1.40, pvalue=0.03) and TTT (HR=1.41, pvalue

Description: INTRODUCTION: Cancer pathogenesis is usually characterized by a long evolutionary process where genomic driver events accumulate over time, conferring advantage to distinct subclones, allowing their expansion and progression. METHODS: To investigate the multiple myeloma (MM) evolutionary history, we characterized the mutational processes' landscape and activity over time utilizing a large cohort of 89 whole genomes and 973 exomes. To improve the accuracy of mutational signatures analysis, we analyzed both the 3' and 5' nucleotide context of each mutation and we developed the novel fitting algorithm mmSig, which fits the entire mutational catalogue of each patient with the mutational signatures involved in MM pathogenesis. The contribution of each mutational signature was then corrected based on the cosine similarity between the original 96-mutational profile and the reconstructed profile generated without that signature. To reconstruct the genetic evolutionary history of each patient's cancer, we integrated two approaches. First dividing all mutations into clonal (early) or subclonal (late), then subdivided the clonal mutations into duplicated mutations (present on two alleles and therefore acquired before the duplication) or non-duplicated mutations (detected on a single allele), reflecting either pre-gain and post-gain mutations on the minor allele, or post-gain mutations acquired on one of the duplicated alleles. RESULTS Eight mutational signatures were identified, seven of which showed significant similarity with the most recent mutational signature catalogue (i.e SBS1, SBS2, SBS5, SBS8, SBS9, SBS13 and SBS18). The new mutational signature (named SBS-MM1) was observed only among relapsed patients exposed to alkylating agents (i.e melphalan). The etiology of this specific signature was further confirmed by analyzing recent whole genomes public data from human-induced pluripotent stem cells exposed to melphalan (Kucab et al, Cell 2019). Reconstructing the chronological activity of each mutational signature, we identified four different routes to acquire the full mutational spectrum in MM based on the differential temporal activity of AID (SBS9) and APOBEC (SBS2 and SBS13). Our data indicate that AID activity is not limited to the first contact with the GC, but persists in the majority of patients, behaving similarly to a B-memory cells, capable of re-entering the germinal center upon antigen stimulation to undergo clonal expansion several times before MM diagnosis. Next, we confirmed the clock-like nature (i.e constant mutation rate) of SBS5 in MM and other post-germinal center disorders such as chronic lymphocytic leukemia and B-cell lymphomas. Based on the SBS5 mutation rates and the corrected ratio between duplicated and non-duplicated mutations within large chromosomal gains, we could time the acquisition of the first copy number gain during the life history of each MM patient. Intriguingly, the first MM chromosomal duplication was acquired on average 38 years (ranges 11-64) before sample collection. In 23/27 (85%) cases the first multi gain event occurred before 30 years of age, and in 13/27 (48%) before 20 years reflecting a long and slow process potentially influenced and accelerated by extrinsic and intrinsic factors. DISCUSSION Our analysis provides a glimpse into the early stages of myelomagenesis, where acquisition of the first key drivers precedes cancer diagnosis by decades. Defining the time window when transformation occurs opens up for new avenues of research: to identify causal mechanisms of disease initiation and evolution, to better define the optimal time to start therapy, and ultimately develop early prevention strategies. Disclosures Bolli: CELGENE: Honoraria; JANSSEN: Honoraria; GILEAD: Other: Travel expenses. Corradini:Janssen: Honoraria, Other: Travel Costs; Jazz Pharmaceutics: Honoraria; KiowaKirin: Honoraria; Servier: Honoraria; Takeda: Honoraria, Other: Travel Costs; Kite: Honoraria; Novartis: Honoraria, Other: Travel Costs; Gilead: Honoraria, Other: Travel Costs; Roche: Honoraria; Sanofi: Honoraria; BMS: Other: Travel Costs. Anderson:Janssen: Consultancy, Speakers Bureau; Takeda: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Bristol-Myers Squibb: Other: Scientific Founder; Oncopep: Other: Scientific Founder; Amgen: Consultancy, Speakers Bureau; Sanofi-Aventis: Other: Advisory Board. Moreau:Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria. Papaemmanuil:Celgene: Research Funding. Avet-Loiseau:takeda: Consultancy, Other: travel fees, lecture fees, Research Funding; celgene: Consultancy, Other: travel fees, lecture fees, Research Funding. Munshi:Adaptive: Consultancy; Amgen: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Takeda: Consultancy; Oncopep: Consultancy; Abbvie: Consultancy. Landgren:Karyopharm: Membership on an entity's Board of Directors or advisory committees; Theradex: Other: IDMC; Adaptive: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Other: IDMC; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding.

Description: Mantle cell lymphoma (MCL) is a mature B-cell neoplasm initially driven by CCND1 rearrangement with 2 molecular subtypes, conventional MCL (cMCL) and leukemic non-nodal MCL (nnMCL), that differ in their clinicobiological behavior. To identify the genetic and epigenetic alterations determining this diversity, we used whole-genome (n = 61) and exome (n = 21) sequencing (74% cMCL, 26% nnMCL) combined with transcriptome and DNA methylation profiles in the context of 5 MCL reference epigenomes. We identified that open and active chromatin at the major translocation cluster locus might facilitate the t(11;14)(q13;32), which modifies the 3-dimensional structure of the involved regions. This translocation is mainly acquired in precursor B cells mediated by recombination-activating genes in both MCL subtypes, whereas in 8% of cases the translocation occurs in mature B cells mediated by activation-induced cytidine deaminase. We identified novel recurrent MCL drivers, including CDKN1B, SAMHD1, BCOR, SYNE1, HNRNPH1, SMARCB1, and DAZAP1. Complex structural alterations emerge as a relevant early oncogenic mechanism in MCL, targeting key driver genes. Breakage-fusion-bridge cycles and translocations activated oncogenes (BMI1, MIR17HG, TERT, MYC, and MYCN), generating gene amplifications and remodeling regulatory regions. cMCL carried significant higher numbers of structural variants, copy number alterations, and driver changes than nnMCL, with exclusive alterations of ATM in cMCL, whereas TP53 and TERT alterations were slightly enriched in nnMCL. Several drivers had prognostic impact, but only TP53 and MYC aberrations added value independently of genomic complexity. An increasing genomic complexity, together with the presence of breakage-fusion-bridge cycles and high DNA methylation changes related to the proliferative cell history, defines patients with different clinical evolution.

Description: Introduction Recent large scale genomic studies have disclosed the heterogeneity of the mutational landscape of chronic lymphocytic leukemia (CLL). The remarkable genomic plasticity of this disease has been further emphasized by the complex subclonal composition recognized in some tumors. Initial studies using high-coverage next generation sequencing (NGS) have revealed the prognostic impact of mutations at very low allelic frequency. The results of these studies have opened a new perspective where the proportion of cells carrying specific driver mutations rather than just the presence or absence of the alterations may be relevant to understand the evolution of this disease. However, the information generated has been limited to a small subset of CLL driver genes. The aims of this study were to define the deep mutational architecture of 28 frequently altered driver genes in CLL and determine the relevance of the subclonal quantitative composition in the progression of the disease. Methods Highly purified tumor samples from 406 untreated CLL patients were included in this study. Ultra-deep NGS of the 28 target genes was performed using the Acces-Array system (Fluidigm) (ATM, TP53, SF3B1, BIRC3, XPO1, RPS15, FBXW7, DDX3X, POT1, KLHL6, MGA, MYD88, IRF4, BRAF, NXF1, BCOR, ZNF292, NRAS, KRAS, CCND2, TRAF3, ZMYM3, MED12) or the Nextera-XT DNA library preparation kit (Illumina) (NOTCH1, NFKBIE, EGR2, PIM1, DTX1) before sequencing in a MiSeq (Illumina). A robust bioinformatic pipeline followed by an extensive verification process allowed the detection of mutations down to 0.3% of variant allele frequency (VAF). Copy number alterations were investigated by high density SNP-arrays in 376 cases. We calculated the cancer cell fraction (CCF) carrying each specific mutation using the PyClone algorithm. The prognostic impact of the mutations was evaluated for time to first treatment (TTFT) and overall survival from the time of sampling. Results The mutational frequency observed for virtually all genes was higher than in similar previous studies of population based CLL at diagnosis. We detected mutations with a VAF below the Sanger sequencing threshold (VAF 80%) was only identified in half of the patients (127, 49%). Convergent mutational evolution, defined as the acquisition of independent genetic mutations in the same gene, was observed in 19 (68%) of the 28 genes analyzed, being present in 66/260 (25%) mutated cases. The number of cases with convergent evolution was directly related to the global mutational frequency of the gene. The clinical relevance of the mutations appeared to be gene specific and related to the quantitative magnitude of the different subclones. We identified three major patterns of specific gene CCF that influenced the prognosis of the patient: 1) CCF independent pattern in which the mere detection of a mutation at any CCF conferred an adverse prognosis (TP53, ATM, POT1, NFKBIE, XPO1, or RPS15 among others); 2) CCF gradual pattern in which the poor prognostic impact was a continuous variable directly related to the size of the mutated clone (SF3B1); and 3) CCF clonal pattern in which the prognostic impact of the mutations was a categorical variable defined by a certain threshold of the mutated clone (NOTCH1, BIRC3, EGR2, FBXW7). On the other hand, cases with convergent mutational evolution had a tendency to a shorter TTFT when compared to mutated cases without this phenomenon. Conclusions In conclusion, the emergence of subclonal mutations is a general and dynamic phenomenon in CLL that seems to involve virtually all driver genes and occurs at different time points of the disease. The clinical impact of the clonal architecture of the tumor is gene specific and related to the magnitude of the respective subclone. These findings provide new insights on the relevance of the subclonal mutational profile in CLL and the importance of quantitative mutational analyses for the management of the patients. Disclosures No relevant conflicts of interest to declare.