Kurzfassung: In chronic lymphocytic leukemia (CLL) short telomeres are associated with other adverse prognostic factors and poor survival. We and others have described association of telomere length with genomic complexity and clonal evolution in CLL. To understand if telomere shortening rather than being only a marker of cell proliferation, could also functionally contribute to disease progression, we generated Terc knock out in the Eµ-TCL1 murine CLL model (Eµ-TCL1 mTerc-/- mice). Comparison of the Eµ-TCL1 mTerc-/- mice from the generations G1, G2 and G3 with that of Eµ-TCL1 (TCL1+) did not show a difference in disease initiation, progression as well as survival even though a significant decrease in telomere length of tumor cells was observed with increasing generations. Of interest, the Eµ-TCL1 mTerc-/- G3 tumors (n=8; G3) more frequently showed defective DNA damage response compared to TCL1+ tumors (n=8), as analysed by changes in phosphorylation of gamma-H2AX, ATM and p53 measured by FACS at 1, 3, 6, 16 and 24 hours after gamma irradiation. Despite this predisposition to undergo genomic complexity, the G3 mice showed no difference in disease development compared to TCL1+ mice. Therefore we investigated if cell extrinsic factors in Terc-/- mice could affect tumor development. The Terc-/- microenvironment is known to be restrictive to B and T-lymphopoiesis and could hence inhibit CLL development. To study the impact of Terc-/- microenvironment, splenic tumors from the Eµ-TCL1 mTerc-/- G3 (n=11; G3) mice were transferred into syngeneic Terc+/+ C57Bl6 mice and compared with that of TCL1+ (n=11). No significant difference in disease burden and survival was observed between these 2 cohorts, indicating that there is no adverse influence of the Terc-/- microenvironment on the tumor growth in the Eµ-TCL1 mTerc-/- mice. Further, we hypothesized that the telomere length in the G3 mice may not be short enough to induce genomic instability and enhance disease aggressiveness. The mice were thus crossed to obtain the Eµ-TCL1 mTerc-/- generation G4 (G4). Though the survival of these mice were similar to that of Eµ-TCL1 controls (median survival :49 vs. 51 weeks; P=0.301), the G4 mice showed significantly decreased disease burden as measured by spleen weight, liver weights and tumor cell fraction. The G4 mice showed decreased fertility and hence further crosses to generate G5 were not performed. However, further shortening of telomeres was achieved by serially transplanting the tumors from G3 into syngeneic recipient mice for 2 generations. Telomere length of the tumor cells analysed by Q-PCR showed a significant decrease with increasing transfer rounds, compared to primary TCL1+ tumors. Interestingly, the 2nd round transfer of the G3 tumors led to a less severe disease and significantly longer survival of the recipient mice compared to 2nd round TCL1+ tumors transplants (median survival from date of transplantation: 15 vs. 7 weeks; P=0.030), indicating that cell intrinsic factors in the G3 tumors hamper proliferation of these cells. We finally analyzed if absence of telomerase could mask disease aggressiveness of the G3 tumors by crossing the G3 mice with wildtype Terc+/+ mice. The resulting TCL1+ mTerc+/- G4 mice showed an increased telomerase activity but had significantly shorter telomere length compared to TCL1+ mice. Strikingly, the TCL1+ mTerc+/- G4 mice showed faster disease development and significantly shorter survival (median survival: 42 vs. 51 weeks; p 〈 0.001) as compared to TCL1+ mice. The aggressiveness of the TCL1+ mTerc+/- G4 tumors was further verified using adoptive transfer into syngeneic mice, and mice transplanted with these tumors showed a significantly shorter survival as compared to TCL1+ or G3 tumors. In summary, the TCL1+ mTerc-/- mice crossed through generations G1 to G4 did not show a difference in disease initiation, progression or survival despite significant shortening of telomeres. However, the tumors from G3 had defective DDR, indicating a potential for accumulating genetic aberrations and clonal evolution. But the absence of functional telomerase decreased the growth potential of these genomic instable tumors. Reconstitution of telomerase in G3 mice resulted in aggressive tumors with short telomere length and could therefore be a valuable murine model for genomic instability and aggressive CLL. Disclosures Tausch: Roche: Consultancy, Honoraria, Speakers Bureau; AbbVie: Consultancy, Honoraria, Other: travel support, Speakers Bureau. Schneider:Celgene: Other: travel grant. Döhner:AbbVie, Agios, Amgen, Astellas, Astex, Celator, Janssen, Jazz, Seattle Genetics: Consultancy, Honoraria; AROG, Bristol Myers Squibb, Pfizer: Research Funding; Celgene, Novartis, Sunesis: Honoraria, Research Funding. Stilgenbauer:AbbVie, AstraZeneca, Celgene, Gilead Sciences, Inc., GSK, Hoffmann La-Roche, Janssen, Novartis: Consultancy, Honoraria, Research Funding, Speakers Bureau.

Kurzfassung: Chronic lymphocytic leukemia (CLL) is characterized by the existence of subsets of patients with (quasi)identical, stereotyped B-cell receptor (BcR) immunoglobulins. Patients in certain major stereotyped subsets often display remarkably consistent clinicobiological profiles, suggesting that the study of BcR immunoglobulin stereotypy in CLL has important implications for understanding disease pathophysiology and refining clinical decision-making. Nevertheless, several issues remain open, especially pertaining to the actual frequency of BcR immunoglobulin stereotypy and major subsets, as well as the existence of higher-order connections between individual subsets. To address these issues, we investigated clonotypic IGHV-IGHD-IGHJ gene rearrangements in a series of 29 856 patients with CLL, by far the largest series worldwide. We report that the stereotyped fraction of CLL peaks at 41% of the entire cohort and that all 19 previously identified major subsets retained their relative size and ranking, while 10 new ones emerged; overall, major stereotyped subsets had a cumulative frequency of 13.5%. Higher-level relationships were evident between subsets, particularly for major stereotyped subsets with unmutated IGHV genes (U-CLL), for which close relations with other subsets, termed “satellites,” were identified. Satellite subsets accounted for 3% of the entire cohort. These results confirm our previous notion that major subsets can be robustly identified and are consistent in relative size, hence representing distinct disease variants amenable to compartmentalized research with the potential of overcoming the pronounced heterogeneity of CLL. Furthermore, the existence of satellite subsets reveals a novel aspect of repertoire restriction with implications for refined molecular classification of CLL.

Kurzfassung: Cancer heterogeneity at the proteome level may explain differences in therapy response and prognosis beyond the currently established genomic and transcriptomic-based diagnostics. The relevance of proteomics for disease classifications remains to be established in clinically heterogeneous cancer entities such as chronic lymphocytic leukemia (CLL). Here, we characterize the proteome and transcriptome alongside genetic and ex-vivo drug response profiling in a clinically annotated CLL discovery cohort (n = 68). Unsupervised clustering of the proteome data reveals six subgroups. Five of these proteomic groups are associated with genetic features, while one group is only detectable at the proteome level. This new group is characterized by accelerated disease progression, high spliceosomal protein abundances associated with aberrant splicing, and low B cell receptor signaling protein abundances (ASB-CLL). Classifiers developed to identify ASB-CLL based on its characteristic proteome or splicing signature in two independent cohorts (n = 165, n = 169) confirm that ASB-CLL comprises about 20% of CLL patients. The inferior overall survival in ASB-CLL is also independent of both TP53- and IGHV mutation status. Our multi-omics analysis refines the classification of CLL and highlights the potential of proteomics to improve cancer patient stratification beyond genetic and transcriptomic profiling.

Kurzfassung: Background: Chronic lymphocytic leukemia (CLL) is the most common adult leukemia in the western world and shows a very heterogeneous clinical course. While the genetic landscape of CLL has been well characterized during recent years it can only partially explain the underlying biology of this heterogeneity. Proteogenomics could offer a valuable tool to fill this gap and improve the understanding of CLL biology. Methods: Here, we performed a large proteogenomic analysis (n=263) of three clinically annotated CLL cohorts: For the discovery cohort (Germany_1: n=68) we performed in-depth HiRIEF LC-MS based proteomics (more than 9000 proteins quantified) alongside genome-, transcriptome and ex-vivo drug response-profiling with 43 clinically established drugs. The proteome of two additional validation cohorts (Germany_2: n=44, Sweden_1: n=89), were characterized by data-independent acquisition (DIA) mass spectrometry. Results: To connect the CLL genotype with the molecular phenotype, we investigated associations between recurrent genetic alterations of CLL, mRNA expression and protein abundance. We found that trisomy 12, IGHV status and SF3B1 mutations had the greatest impact on protein abundances. CLL specific recurrent chromosomal deletions and gains (trisomy 12, del17p, del13q, del11q, gain8q24) consistently impacted on gene expression and protein abundance through gene dosage effects. We explored functional consequences of these gene dosage effects and found that the additional copy of chromosome 12 increased the abundance of central B-cell receptor (BCR) protein complexes through cis- and trans-effects, which could explain the increased response of trisomy 12 patient samples to BCR inhibition. Somatic mutations of TP53, ATM and XPO1 were associated with less, but specific and biologically-relevant protein abundance changes. p53 for instance, was the most upregulated protein in TP53 mutated samples, owing to the known stabilisation of mutant p53. This effect was not detectable on transcript level. ATM and XPO1 protein abundances were significantly lower in ATM and XPO1 mutated cases, indicating loss-of-function phenotypes of these mutations. To understand global similarities and differences between CLL patients on the proteomic level, we performed unsupervised clustering and identified clinically meaningful subgroups. Unsupervised clustering of the proteomics data identified six subgroups with contrasting clinical behaviour. TP53 mutations, IGHV status, trisomy 12 and their interactions explained five subgroups. These results show that quantitative mass spectrometry-based proteomics distinguished clinically relevant subgroups of CLL. Most importantly, we identified a previously unappreciated subgroup of CLL, comprising 20% of all cases, which could be uncovered by proteomic profiling and showed no association with frequent genetic or transcriptional alterations. This new CLL subgroup was characterized by accelerated disease progression, SF3B1 mutation-independent splicing alterations, metabolomic reprogramming and increased vulnerability to inhibitors of metabolic enzymes and the proteasome. Surprisingly, major BCR signaling proteins were downregulated in this subgroup, suggesting less dependence on BCR activity. In accordance with this observation, an unsupervised analysis revealed that low levels of many BCR signaling proteins (e.g. PLCG2 and PIK3CD) were associated with short time to next treatment. The existence of this subgroup could be confirmed in the validation cohorts. Finally, we performed an unsupervised multi-omics factor analysis (MOFA) across all omics data sets in parallel. This unsupervised analysis confirmed the existence of the above identified CLL subgroups and an important role of SF3B1 mutation-independent splicing alterations in CLL. Conclusion: Our integrative multi-omics analysis provides the first comprehensive overview of the interplay between genetic variants, the transcriptome, and the proteome, along with functional consequences for drug response and clinical outcome in CLL. Importantly, we identified a new subgroup with accelerated disease progression, a distinct proteomic signature and a clinically exploitable drug sensitivity profile. Figure Disclosures Mueller-Tidow: BiolineRx: Research Funding; Daiichi Sankyo: Research Funding; Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding; BMBF: Research Funding; Wilhelm-Sander-Stiftung: Research Funding; Jose-Carreras-Siftung: Research Funding; Bayer AG: Research Funding; Deutsche Krebshilfe: Research Funding; Deutsche Forschungsgemeinschaft: Research Funding; Janssen-Cilag Gmbh: Membership on an entity's Board of Directors or advisory committees. Dreger:Neovii: Research Funding; Roche: Consultancy, Speakers Bureau; Riemser: Consultancy, Research Funding, Speakers Bureau; Novartis: Consultancy, Speakers Bureau; Janssen: Consultancy; Gilead: Consultancy, Speakers Bureau; AstraZeneca: Consultancy; AbbVie: Consultancy, Speakers Bureau. Stilgenbauer:Pharmacyclics: Consultancy, Honoraria, Other, Research Funding; Novartis: Consultancy, Honoraria, Other, Research Funding; Mundipharma: Consultancy, Honoraria, Other, Research Funding; Janssen-Cilag: Consultancy, Honoraria, Other: travel support, Research Funding; GlaxoSmithKline: Consultancy, Honoraria, Other: travel support, Research Funding; Gilead: Consultancy, Honoraria, Other: travel support, Research Funding; Genzyme: Consultancy, Honoraria, Other: travel support, Research Funding; Genentech: Consultancy, Honoraria, Other: travel support, Research Funding; F. Hoffmann-LaRoche: Consultancy, Honoraria, Other: travel support, Research Funding; Celgene: Consultancy, Honoraria, Other: travel support, Research Funding; Boehringer-Ingelheim: Consultancy, Honoraria, Other: travel support, Research Funding; Amgen: Consultancy, Honoraria, Other: travel support, Research Funding; AbbVie: Consultancy, Honoraria, Other: travel support, Research Funding. Tausch:Roche: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria, Research Funding; Janssen-Cilag: Consultancy, Honoraria, Research Funding. Dietrich:Roche: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; KITE: Membership on an entity's Board of Directors or advisory committees.