Biology and Treatment of High-Risk CLL: Significance of Complex Karyotype

Several reports highlight the clinical significance of cytogenetic complexity, namely, complex karyotype (CK) identified though the performance of chromosome banding analysis (CBA) in chronic lymphocytic leukemia. Indeed, apart from a number of studies underscoring the prognostic and predictive value of CK in the chemo(immune)therapy era, mounting evidence suggests that CK could serve as an independent prognosticator and predictor even in patients treated with novel agents. In the present review, we provide an overview of the current knowledge regarding the clinical impact of CK in CLL, touching upon open issues related to the incorporation of CK in the clinical setting.

Multiplex ligation-dependent probe amplification identifies copy number changes in normal and undetectable karyotype MDS patients

Chromosomal abnormalities play an important role in classification and prognostication of myelodysplastic syndrome (MDS) patients. However, more than 50% of low-risk MDS patients harbor a normal karyotype. Recently, multiplex ligation-dependent probe amplification (MLPA) has emerged as an effective and robust method for the detection of cytogenetic aberrations in MDS patients. To characterize the subset of MDS with normal karyotype or failed chromosome banding analysis, we analyzed 144 patient samples with normal karyotype or undetectable through regular chromosome banding analysis, which were subjected to parallel comparison via fluorescence in situ hybridization (FISH) and MLPA. MLPA identifies copy number changes in 16.7% of 144 MDS patients, and we observed a significant difference in overall survival (OS) (median OS: undefined vs 27 months, p=0.0071) in patients with normal karyotype proved by MLPA versus aberrant karyotype cohort as determined by MLPA. Interestingly, patients with undetectable karyotype via regular chromosome banding indicated inferior outcome. Collectively, MDS patients with normal or undetectable karyotype via chromosome banding analysis can be further clarified by MLPA, providing more prognostic information that benefit for individualized therapy.

Chromosome banding analysis and genomic microarrays are both useful but not equivalent methods for genomic complexity risk stratification in chronic lymphocytic leukemia patients

Genome complexity has been associated with poor outcome in patients with chronic lymphocytic leukemia (CLL). Previous cooperative studies established five abnormalities as the cut-off that best predicts an adverse evolution by chromosome banding analysis (CBA) and genomic microarrays (GM). However, data comparing risk stratification by both methods are scarce. Herein, we assessed a cohort of 340 untreated CLL patients highly enriched in cases with complex karyotype (CK, 46.5%) with parallel CBA and GM studies. Abnormalities found by both techniques were compared. Prognostic stratification in three risk groups based on genomic complexity [0-2, 3-4 and ≥5 abnormalities] was also analyzed. No significant differences in the percentage of patients classified into each category were detected, but only a moderate agreement was observed between methods when focusing in individual cases (κ=0.507; p

Multiplex ligation-dependent probe amplification identifies copy number changes in normal and undetectable karyotype MDS patients

Background Chromosomal abnormalities play an important role in classification and prognostication of myelodysplastic syndromes (MDS) patients. However, more than 50% low risk MDS patients harbor a normal karyotype. Recently, multiplex ligation-dependent probe amplification (MLPA) has emerged as an effective and robust method for the detection of cytogenetic aberrations in MDS patients. Methods To characterize the subset of MDS with normal karyotype or failed chromosome banding analysis, we analyzed 144 patient samples with normal karyotype or undetectable through regular chromosome banding, which were subjected to parallel comparison via fluorescence in situ hybridization (FISH) and MLPA. Results MLPA identifies copy number changes in 16.7% of 144 MDS patients and we observed a significant difference in overall survival (OS) (median OS: undefined vs 27 months, p=0.0071) in patients with normal karyotype proved by MLPA, versus aberrant karyotype cohort as determined by MLPA. Interestingly, patients with undetectable karyotype via regular chromosome banding indicated inferior outcome. Conclusion Collectively, MDS patients with normal or undetectable karyotype via chromosome banding analysis can be further clarified by MLPA, providing more prognostic information that benefit for individualized therapy.

Artificial Intelligence Substantially Supports Chromosome Banding Analysis Maintaining Its Strengths in Hematologic Diagnostics Even in the Era of Newer Technologies

Background: Chromosome banding analysis (CBA) is one of the most important techniques in diagnostics and prognostication in hematologic neoplasms. CBA is still a challenging method with very labor-intensive wet lab processes and karyotyping that requires highly skilled and experienced specialists for tumor cytogenetics. Short turnaround times (TAT) are becoming increasingly important to enable genetics-based treatment stratification at diagnosis. Aim: Improve TAT and quality of CBA by automated wet lab processes and AI-based algorithms for automatic karyotyping. Methods: In the last 15 years the CBA workflow has gradually been automated with focus on the wet lab and metaphase capturing processes. Now, a retrospective unselected digital data set of 100,000 manually arranged karyograms (KG) with normal karyotype (NKG) from routine diagnostics was used to train a deep neural network (DNN) classifier to automatically determine the class/number and orientation of the respective chromosomes (AI based classifier normal, AI-CN). With a total of 6 Mio parameters, the DNN uses two distinct output layers to simultaneously predict the chromosome number (24 classes) and the angle that is required to rotate the chromosome in its correct, vertical position (360 classes). Training of the DNN took 16 days on a Nvidia RTX 2080 Ti graphic card with 4352 cores. AI-CN was implemented into the routine workflow (including ISO 15189) after 7 months of development and intensive testing. Results: The AI-CN was tested by highly experienced staff in an independent prospective validation set of 500 NKG: 22,675/23,000 chromosomes (98.6%) were correctly assigned by AI-CN. In 369/500 (73.8%) of cells all chromosomes were correctly assigned, in an additional 20% only 2 chromosomes were interchanged. The chromosomes accounting for the majority of misclassifications were chromosomes 14 and 15 as well as 4 and 5, which are difficult to distinguish in poor quality metaphases also for humans. The 1st AI-CN was implemented into routine diagnostics in August 2019 and the 2nd AI-CN - optimized for chromosome orientation - was used since November 2019. Since then more than 17,500 cases have been processed with AI-CN (>350,000 metaphases) in routine diagnostics resulting in the following benefits: 1) Reduced working time: an experienced cytogeneticist needs - depending on chromosome quality - between 1 and 3 minutes to arrange a KG, while AI-CN needs only 1 second and the cytogeneticist about 30 seconds to review the KG. 2) Shorter TAT: The proportion of cases reported within 5 days increased from 30% before AI-CN (2019) to 36% with AI-CN1 (2019) and 45% with AI-CN2 (2019/2020), while the proportion of cases reported >7 days was reduced to 28%, 21%, and 17%, respectively (figure). Using AI-CN for aberrant karyotypes results in correct assignment of normal chromosomes and thus also correct KG in cases with solely numerical chromosome abnormalities. Derivative chromosomes derived from structural abnormalities (SA) that differ clearly from any normal chromosome are not automatically assigned but are left out for manual classification. Thus, even in cases with SA, using AI-CN saves time. To allow AI based SA assignment, two additional classifiers normal/aberrant (CNA) were built: AI-CNA1 was trained on 54,634 KG encompassing 10 different SA (AKG) and 100,000 NKG and AI-CNA2 was trained on all AKG and an equal number of NKG. First validation tests are promising and optimization is ongoing. Once the CNA has been optimized, a standardized high quality of chromosome aberration detection is feasible. A fully automated separation of chromosomes is currently in progress and will reduce the TAT by another 12-24 hours. In a fully automated workflow the detection of small subclones can be further optimized by increasing today's standard of 20 metaphases to several hundred, even without any delay in TAT and need for additional personnel. Conclusions: Implementation of AI in CBA substantially improves the quality of results and shortens turnaround times even in comparison to highly trained and experienced cytogeneticists. In the majority of cases a complete karyotype analysis can be guaranteed within 3 to 7 days, allowing CBA based treatment strategies at diagnosis. This fully automated workflow can be implemented worldwide, is rapidly scalable, can be performed cloud based and requires in the near future fewer experienced tumor cytogeneticists. Figure Disclosures Hänselmann: MetaSystems: Current Employment. Lörch:MetaSystems: Current equity holder in private company.

Multiplex ligation-dependent probe amplification identifies copy number changes in normal and undetectable karyotype MDS patients

Background In myelodysplastic syndromes (MDS), cytogenetic aberrations play an important role for classification and prognostication. However, more than 50% low risk MDS patients harbor a normal karyotype. Recently, multiplex ligation-dependent probe amplification (MLPA) has emerged as an effective and robust method for the detection of cytogenetic aberrations in MDS patients.Methods To characterize the subset of MDS with normal karyotype or failed chromosome banding analysis, we analyzed 144 patient samples with normal karyotype or undetectable through regular chromosome banding, which were subjected to parallel comparison via fluorescence in situ hybridization (FISH) and MLPA.Results MLPA identifies copy number changes in 16.7% of 144 MDS patients and we observed a significant difference in overall survival (OS) (median OS: undefined vs 27 months, p=0.0071) in patients with normal karyotype proved by MLPA, versus aberrant karyotype cohort as determined by MLPA. Interestingly, patients with undetectable karyotype via regular chromosome banding indicated inferior outcome. Conclusion Collectively, MDS patients with normal or undetectable karyotype via chromosome banding analysis can be further clarified by MLPA, providing more prognostic information that benefit for individualized therapy.

Genomic arrays identify high-risk chronic lymphocytic leukemia with genomic complexity: a multi-center study

Complex karyotype (CK) identified by chromosome-banding analysis (CBA) has shown prognostic value in chronic lymphocytic leukemia (CLL). Genomic arrays offer high-resolution genome-wide detection of copy-number alterations (CNAs) and could therefore be well equipped to detect the presence of a CK. Current knowledge on genomic arrays in CLL is based on outcomes of single center studies, in which different cutoffs for CNA calling were used. To further determine the clinical utility of genomic arrays for CNA assessment in CLL diagnostics, we retrospectively analyzed 2293 arrays from 13 diagnostic laboratories according to established standards. CNAs were found outside regions captured by CLL FISH probes in 34% of patients, and several of them including gains of 8q, deletions of 9p and 18p (p<0.01) were linked to poor outcome after correction for multiple testing. Patients (n=972) could be divided in three distinct prognostic subgroups based on the number of CNAs. Only high genomic complexity (high-GC), defined as ≥5 CNAs emerged as an independent adverse prognosticator on multivariable analysis for time to first treatment (Hazard ratio: 2.15, 95% CI: 1.36-3.41; p=0.001) and overall survival (Hazard ratio: 2.54, 95% CI: 1.54-4.17; p<0.001; n=528). Lowering the size cutoff to 1 Mb in 647 patients did not significantly improve risk assessment. Genomic arrays detected more chromosomal abnormalities and performed at least as well in terms of risk stratification compared to simultaneous chromosome banding analysis as determined in 122 patients. Our findings highlight genomic array as an accurate tool for CLL risk stratification.

Chromosome Banding Analysis Versus Genomic Microarrays: A Comparison of Methods for Genomic Complexity Risk Stratification in Chronic Lymphocytic Leukemia Patients with Complex Karyotype

INTRODUCTION. Chromosome banding analysis (CBA) is the gold standard to identify complex karyotypes (CK; ≥3 chromosomal aberrations in the same clone). CK are predictors of poor prognosis and treatment refractoriness in patients with chronic lymphocytic leukemia (CLL). Patients with CK (15% at diagnosis) constitute a heterogeneous subgroup with highly variable clinical course. Recent studies that aim to refine CK definition in CLL suggest that ≥5 is the number of anomalies detected by CBA that better predicts an impaired outcome (Baliakas et al, 2019). Molecular techniques as genomic microarrays also detect genomic complexity (GC). A recent multicentric ERIC study (Leeksma et al, ASH 2017) identified that patients with ≥5 copy number alterations (CNA) detected by microarrays are associated with an adverse outcome. However, risk stratification regarding genomic complexity assessed by CBA and microarrays has not been compared. OBJECTIVES. 1. To compare genomic complexity in CLL defined by CBA vs microarrays; 2. To compare risk stratification based on genomic complexity measured by both techniques. METHODS. The study cohort included 293 CLL patients from 16 European institutions (67% males) with available CBA result at diagnosis or prior to first treatment. The cohort was enriched in patients with CK (n=153, 52%). Tumor DNA extracted from peripheral blood (n=254) or bone marrow samples (n=39) obtained at the time of CBA was hybridized to CGH-arrays (n=12) and SNP-arrays (n=281) platforms. Clinically relevant aberrations [11q-, +12, 13q-, 17p-] and CNA ≥5Mb were considered for the anomaly count. Three risk groups were defined using previously suggested cut-off points for CBA and microarrays [non-CK/low-GC: 0-2; low/intermediate-CK/GC: 3-4; high-CK/GC: ≥5 (Baliakas et al, Leeksma et al)]. Groups obtained by both methods were compared and correlated with other clinical and biological data. Time to first treatment (TTT) of patients categorized according to the number of alterations detected by CBA and microarrays was analyzed. RESULTS. Median number of abnormalities detected was 3 (range: 0-19) by CBA and 2 (range: 0-18) by microarrays. When stratified according to previously defined criteria, a moderate agreement was observed between both techniques (κ=0.483, p<0.001). Remarkably, 8/74 (11%) of patients with high-CK were considered low-GC by microarrays while none of the 140 patients with non-CK was classified as high-GC by microarrays (Table 1). Discordances in those 8 cases underestimated by microarrays were due to the presence of chromosome markers or complex rearrangements in the karyotype which were globally balanced or to subclonal aberrations expanded during CBA culture but represented in a minor proportion of the whole sample. Regarding the prognostic value of genomic complexity and considering the number of abnormalities detected as a continuous variable, CBA and microarrays showed a similar concordance index (C-index) for TTT (0.615 vs 0.609, respectively). When considering all the abnormalities independently of their size or when lowering the cutoff to 1Mb for those non-CLL abnormalities, similar impact on TTT was observed (C-index=0.593 vs 0.616). The three risk groups defined by each method showed significant differences on TTT (Figure 1, p<0.001). In discordant cases, significant differences on TTT were only observed in cases with high-CK, where low-GC and high-GC showed poor outcome when compared to intermediate-GC group (Figure 2, p=0.009). As genomic complexity category increased in both techniques, a significant increment of del/mutTP53 (CBA: 13% vs 29% vs 62%, p<0.001; microarrays: 16% vs 26% vs 68%, p<0.001) and unmutated IGHV (U-IGHV) (CBA: 49% vs 59% vs 71%, p=0.015; microarrays: 47% vs 68% vs 73%, p=0.001) cases was observed. Of note, among the 8 high risk patients underscored by microarrays, 3 showed del/mutTP53 and 6 showed U-IGHV. Additional techniques, as chromosome painting, are ongoing to confirm microarray results and find an explanation for discordances. CONCLUSIONS. 1. CBA and microarrays are helpful techniques for assessing genomic complexity in CLL patients; 2. Risk categories established by both methods have a significant impact on TTT although they show a moderate agreement; 3. Discordant cases are being investigated to refine genomic complexity criteria equivalent by both techniques. ACKNOWLEDGEMENTS. 17SGR437, GLD17/00282, FPU17/00361 Disclosures Rigolin: AbbVie: Speakers Bureau; Gilead: Speakers Bureau; Gilead: Research Funding. Gimeno:JANSSEN: Consultancy, Speakers Bureau; Abbvie: Speakers Bureau. Bosch:Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; AstraZeneca: Honoraria, Research Funding; Takeda: Honoraria, Research Funding; F. Hoffmann-La Roche Ltd/Genentech, Inc.: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Acerta: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Kyte: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Honoraria, Research Funding. Cuneo:Amgen: Honoraria; Abbvie: Honoraria, Speakers Bureau; Gilead: Honoraria, Speakers Bureau; Janssen: Honoraria, Speakers Bureau; Roche: Honoraria, Speakers Bureau. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

EFFICACY OF OLIGONUCLEOTIDE DSP30 IN COMBINATION WITH INTERLEUKIN-2 FOR THE DETECTION OF CHROMOSOMAL ABERRATIONS IN PATIENTS WITH CHRONIC LYMPHOCYTIC LEUKEMIA

Aim.To evaluate the efficacy of DSP30 in combination with IL2 in cultivating blood cells/bone marrow/lymph nodes in chronic lymphocytic leukemia (CLL) patients to detect clonal abnormalities.Materials and methods.The study included 50 patients with CLL, all of whom underwent both chromosome banding analysis (CBA) (46 patients with DSP30+IL2 and LPS+TPA; 4 patients with only DSP30+IL2) and FISH with DNA probes to detect trisomy 12 and deletions of 13q14, 11q22 and 17p13.Results.Under cell cultivation with DSP30+IL2 and LPS+TPA, CBA was successfully performed in 41 (82 %) and 38 (83 %) patients. Chromosome aberrations were observed in 36 (72 %) and 15 (33%) cases, while a complex karyotype was detected in 13 (26%) and 5 (11%) cases, respectively. A significant difference was found between the number of metaphases with chromosomal abnormalities obtained by cultivation with DSP30+IL2 and LPS+TPA (V = 490.5, p < 0.05). CBA revealed balanced translocations in 6 patients, with the involvement of the IgH/14q324 locus being confirmed in 4 cases. Unbalanced translocations and various combinations of translocations were detected in 11 and 6 patients, respectively. In 5 cases, according to CBA, the results of 13q14, 11q22, 17p13 deletions identified by FISH were accompanied by balanced or unbalanced translocations in these loci. Unbalanced t(12;16)(q14;q23) — a case of partial trisomy — was detected only by CBA with DSP30+IL2.Conclusions.An abnormal karyotype was detected in CLL patients twice as more frequently under cultivation with DSP30+IL2 compared to LPS+TPA. CBA is an important method allowing the structure of chromosomal abnormalities to be specified and translocations to be identified. As a result, patients running the highest risk of CLL — those with a complex karyotype — can be singled out for selecting an optimal strategy of their management.

Targeted RNA Sequencing Is Capable of Identifying Thus Far Unknown Partner Genes in Leukemias with Rare Translocations and Provides Important Clinical and Therapeutical Information

Background: The genomic landscape of hematological malignancies has been resolved mainly based on whole exome and whole genome sequencing, primarily targeting gene mutations. Beside mutations also gene fusions function as therapeutic targets, impressively shown for e.g. BCR-ABL1 and ETV6-PDGFRB. Hence, the need for a comprehensive genetic analysis is increasing, as it is the basis for precision medicine, selecting treatment based on genotype and providing markers for disease monitoring. Aim: To test the value of targeted RNA sequencing in a routine diagnostic work up. Patients and Methods: 38 cases were selected in which rearrangements involving KMT2A (n=8), RUNX1 (n=19), ETV6 (n=9), RARA (n=1) and JAK2 (n=1) had been identified by chromosome banding analysis (CBA) complemented by FISH analysis. In all cases the partner gene could not be identified using standard methods. Targeted RNA sequencing was performed using the TruSight RNA Fusion panel (Illumina, San Diego, CA) consisting of 7690 probes covering 507 genes known to be involved in gene fusions. Library was prepared according to manufacturer's protocol with ~50ng DNA extracted from fresh/frozen samples. This assay allows the capture of all targeted transcripts. Sequencing was performed on two NextSeq runs (Illumina, San Diego, CA) with 20 multiplexed samples including two samples with known fusions as positive control samples. Analysis was performed with the RNA-Seq Alignment App (BaseSpace Sequence Hub) using Star for Alignment and Manta for gene fusion calling with default parameters (Illumina, San Diego, CA). Results: In 22/38 cases with rearrangements involving KMT2A (n=8), RUNX1 (n=8), ETV6 (n=4), RARA (n=1) or JAK2 (n=1) this approach led to important new information: The following partner genes for KMT2A were identified: MLLT10 (n=2), MLLT1 (n=2), ITPR2, FLNC, ASXL2 and ARHGEF12. MLLT10 and MLLT1 are two of the most frequent partner genes of KMT2A, while KMT2A-ARHGEF12 fusions are rare. Fusion of KMT2A to ITPR2, FLNC, or ASXL2 have not been reported yet. Seven different partner genes were identified in RUNX1 translocated cases. These were PLAG1 (n=2), PRDM16, MECOM, ZFPM2, MAN1A2, N6AMT2, and KIAA1549L. PRDM1, MECOM and ZFPM2 have previously been described in the literature as RUNX1 partner genes but were not suspected in our cases as partner genes due to complex cytogenetic rearrangements in CBA. The other identified partner genes have not been described so far. Interestingly, PRDM1, MECOM, ZFPM2 and the newly identified PLAG1 are all members of the C2H2-type zinc finger gene family. Four different partner genes were identified in ETV6 rearranged cases: ABL1, CCDC126, CLPTM1L, and CFLAR-AS1. Most strikingly was the identification of the ETV6-ABL1 fusion, which could not be suspected by cytogenetics as the 5' ETV6 FISH signal was located on chromosome 7. This ETV6-ABL1 fusion was confirmed by conventional RT-PCR. In an ALL patient a JAK2-PPFIBP1 fusion was identified leading to classification as a BCR-ABL1-like ALL. In an APL patient showing an ins(17;11)(q12;q14q23) in chromosome banding analysis a ZBTB16-RARA fusion was identified and thus resistance to all-trans retinoic acid, arsenic trioxide, and anthracyclines can be predicted. All these fusions were not detectable by our routine RT-PCR analyses as these assays cover only the most frequently occurring breakpoints in fusions with known partner genes, but might miss very rare variants. For all yet undescribed fusion partners routine assays are not available. Based on the results of targeted RNA sequencing quantitative PCR assays for MRD monitoring can now be established. In 11 cases with a RUNX1 rearrangement and 5 cases with an ETV6 rearrangement no fusion transcript was identified. Further analyses will have to clarify whether in these cases no transcript was derived from the genomic rearrangement. Conclusions: 1) Targeted RNA sequencing was able to identify and characterize rare gene fusions and thus provided the basis for the design of RT-PCR based assays for monitoring MRD. 2) Targetable genetic aberrations were identified, which were not identifiable by chromosome banding analysis but would now lead to more individualized treatment. 3) Thus, targeted RNA sequencing may be a valuable tool in routine diagnostics for patients with rearrangements unresolved by standard techniques, also paving the way to precision medicine in a considerable number of patients. Disclosures Haferlach: MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Nadarajah:MLL Munich Leukemia Laboratory: Employment. Meggendorfer:MLL Munich Leukemia Laboratory: Employment. Dicht:MLL Munich Leukemia Laboratory: Employment. Stengel:MLL Munich Leukemia Laboratory: Employment. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.