Quality control and quantification in IG/TR next-generation sequencing marker identification: protocols and bioinformatic functionalities by EuroClonality-NGS

Assessment of clonality, marker identification and measurement of minimal residual disease (MRD) of immunoglobulin (IG) and T cell receptor (TR) gene rearrangements in lymphoid neoplasms using next-generation sequencing (NGS) is currently under intensive development for use in clinical diagnostics. So far, however, there is a lack of suitable quality control (QC) options with regard to standardisation and quality metrics to ensure robust clinical application of such approaches. The EuroClonality-NGS Working Group has therefore established two types of QCs to accompany the NGS-based IG/TR assays. First, a central polytarget QC (cPT-QC) is used to monitor the primer performance of each of the EuroClonality multiplex NGS assays; second, a standardised human cell line-based DNA control is spiked into each patient DNA sample to work as a central in-tube QC and calibrator for MRD quantification (cIT-QC). Having integrated those two reference standards in the ARResT/Interrogate bioinformatic platform, EuroClonality-NGS provides a complete protocol for standardised IG/TR gene rearrangement analysis by NGS with high reproducibility, accuracy and precision for valid marker identification and quantification in diagnostics of lymphoid malignancies.This work was supported by Ministry of Health of the Czech Republic, grant no. 16-34272A; computational resources were provided by the CESNET LM2015042 and the CERIT Scientific Cloud LM2015085, provided under the programme “Projects of Large Research, Development, and Innovations Infrastructures”. Analyses in Prague (JT, EF and MS) were supported by Ministry of Health, Czech Republic, grant no. 00064203, and by PRIMUS/17/MED/11. Analyses in the Monza (Centro Ricerca Tettamanti, SS, AG and GC) laboratory were supported by the Italian Association for Cancer Research (AIRC) and Comitato Maria Letizia Verga

Cytogenetic complexity in chronic lymphocytic leukemia: definitions, associations and clinical impact

Recent evidence suggests that complex karyotype (CK) defined by the presence of 653 chromosomal aberrations (structural and/or numerical) identified by chromosome banding analysis (CBA) may be relevant for treatment decision-making in chronic lymphocytic leukemia (CLL). However, many challenges towards routine clinical application of CBA remain. In a retrospective study of 5290 patients with available CBA data, we explored both clinicobiological associations and the clinical impact of CK in CLL. We found that patients with 655 abnormalities, defined as high-CK, exhibit uniformly dismal clinical outcome, independently of clinical stage, TP53 aberrations (deletion of chromosome 17p and or TP53 mutations, TP53abs) and the expression of somatically hypermutated (M-CLL) or unmutated (U-CLL) immunoglobulin heavy variable genes (IGHV). Thus, they contrasted CK cases with 3 or 4 aberrations (low-CK and intermediate-CK, respectively) who followed aggressive disease courses only in the presence of TP53abs. At the other end of the spectrum, patients with CK and +12,+19 displayed an exceptionally indolent profile. Building upon CK, TP53abs and IGHV gene somatic hypermutation status, we propose a novel hierarchical model where patients with high-CK exhibit the worst prognosis, while M-CLL lacking CK or TP53abs as well as CK with +12,+19 show the longest overall survival. In conclusion, CK should not be axiomatically considered unfavorable in CLL, representing a heterogeneous group with variable clinical behavior. High-CK with 655 chromosomal aberrations emerges as prognostically adverse, independently of other biomarkers. Prospective clinical validation is warranted before finally incorporating high-CK in risk stratification of CLL

Functional loss of IKBE leads to NF-KB deregulation in aggressive chronic lymphocytic leukemia

NF-?B is constitutively activated in chronic lymphocytic leukemia (CLL); however, the implicated molecular mechanisms remain largely unknown. Thus, we performed targeted deep sequencing of 18 core complex genes within the NF-?B pathway in a discovery and validation CLL cohort totaling 315 cases. The most frequently mutated gene was NFKBIE (21/315 cases; 7%), which encodes I?B?, a negative regulator of NF-?B in normal B cells. Strikingly, 13 of these cases carried an identical 4-bp frameshift deletion, resulting in a truncated protein. Screening of an additional 377 CLL cases revealed that NFKBIE aberrations predominated in poor-prognostic patients and were associated with inferior outcome. Minor subclones and/or clonal evolution were also observed, thus potentially linking this recurrent event to disease progression. Compared with wild-type patients, NFKBIE-deleted cases showed reduced I?B? protein levels and decreased p65 inhibition, along with increased phosphorylation and nuclear translocation of p65. Considering the central role of B cell receptor (BcR) signaling in CLL pathobiology, it is notable that I?B? loss was enriched in aggressive cases with distinctive stereotyped BcR, likely contributing to their poor prognosis, and leading to an altered response to BcR inhibitors. Because NFKBIE deletions were observed in several other B cell lymphomas, our findings suggest a novel common mechanism of NF-?B deregulation during lymphomagenesis. <br/

Bioinformatic pipelines for whole transcriptome sequencing data exploitation in leukemia patients with complex structural variants

Background Extensive genome rearrangements, known as chromothripsis, have been recently identified in several cancer types. Chromothripsis leads to complex structural variants (cSVs) causing aberrant gene expression and the formation of de novo fusion genes, which can trigger cancer development, or worsen its clinical course. The functional impact of cSVs can be studied at the RNA level using whole transcriptome sequencing (total RNA-Seq). It represents a powerful tool for discovering, profiling, and quantifying changes of gene expression in the overall genomic context. However, bioinformatic analysis of transcriptomic data, especially in cases with cSVs, is a complex and challenging task, and the development of proper bioinformatic tools for transcriptome studies is necessary. Methods We designed a bioinformatic workflow for the analysis of total RNA-Seq data consisting of two separate parts (pipelines): The first pipeline incorporates a statistical solution for differential gene expression analysis in a biologically heterogeneous sample set. We utilized results from transcriptomic arrays which were carried out in parallel to increase the precision of the analysis. The second pipeline is used for the identification of de novo fusion genes. Special attention was given to the filtering of false positives (FPs), which was achieved through consensus fusion calling with several fusion gene callers. We applied the workflow to the data obtained from ten patients with chronic lymphocytic leukemia (CLL) to describe the consequences of their cSVs in detail. The fusion genes identified by our pipeline were correlated with genomic break-points detected by genomic arrays. Results We set up a novel solution for differential gene expression analysis of individual samples and de novo fusion gene detection from total RNA-Seq data. The results of the differential gene expression analysis were concordant with results obtained by transcriptomic arrays, which demonstrates the analytical capabilities of our method. We also showed that the consensus fusion gene detection approach was able to identify true positives (TPs) efficiently. Detected coordinates of fusion gene junctions were in concordance with genomic breakpoints assessed using genomic arrays. Discussion Byapplying our methods to real clinical samples, we proved that our approach for total RNA-Seq data analysis generates results consistent with other genomic analytical techniques. The data obtained by our analyses provided clues for the study of the biological consequences of cSVs with far-reaching implications for clinical outcome and management of cancer patients. The bioinformatic workflow is also widely applicable for addressing other research questions in different contexts, for which transcriptomic data are generated

Distinct p53 phosphorylation patterns in chronic lymphocytic leukemia patients are reflected in the activation of circumjacent pathways upon DNA damage

TP53 gene abnormalities represent the most important biomarker in chronic lymphocytic leukemia (CLL). Altered protein modifications could also influence p53 function, even in the wild‐type protein. We assessed the impact of p53 protein phosphorylations on p53 functions as an alternative inactivation mechanism. We studied p53 phospho‐profiles induced by DNA‐damaging agents (fludarabine, doxorubicin) in 71 TP53‐intact primary CLL samples. Doxorubicin induced two distinct phospho‐profiles: profile I (heavily phosphorylated) and profile II (hypophosphorylated). Profile II samples were less capable of activating p53 target genes upon doxorubicin exposure, resembling TP53‐mutant samples at the transcriptomic level, whereas standard p53 signaling was triggered in profile I. ATM locus defects were more common in profile II. The samples also differed in the basal activity of the hypoxia pathway: the highest level was detected in TP53‐mutant samples, followed by profile II and profile I. Our study suggests that wild‐type TP53 CLL cells with less phosphorylated p53 show TP53‐mutant‐like behavior after DNA damage. p53 hypophosphorylation and the related lower ability to respond to DNA damage are linked to ATM locus defects and the higher basal activity of the hypoxia pathway

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.This study was partly funded by an unrestricted contribution from Janssen Pharmaceuticals and from GILEAD Sciences SA. A.C.L. is supported by the Peters van der Laan foundation. J.C.S. was funded by Bloodwise (11052, 12036), the Kay Kendall Leukaemia Fund (873), Cancer Research UK (C34999/A18087, ECMC C24563/A15581), Wessex Medical Research and the Bournemouth Leukaemia Fund. K.P., M.J., and S.P. are supported by the project MHCR DRO no. 65269705, the research infrastructures NCMG LM2015091, and EATRIS-CZ LM2015064, and the project CEITEC2020 LQ1601, funded by MEYS CR. R.R. is supported by Swedish Cancer Society, the Swedish Research Council, the Knut and Alice Wallenberg Foundation, Karolinska Institutet, Karolinska University Hospital, and Radiumhemmets Forskningsfonder, Stockholm.Peer reviewe