Precision diagnostics in chronic lymphocytic leukemia: Past, present and future

Genetic diagnostics of hematological malignancies has evolved dramatically over the years, from chromosomal banding analysis to next-generation sequencing, with a corresponding increased capacity to detect clinically relevant prognostic and predictive biomarkers. In diagnostics of patients with chronic lymphocytic leukemia (CLL), we currently apply fluorescence in situ hybridization (FISH)-based analysis to detect recurrent chromosomal aberrations (del(11q), del(13q), del(17p) and trisomy 12) as well as targeted sequencing (IGHV and TP53 mutational status) for risk-stratifying purposes. These analyses are performed before start of any line of treatment and assist in clinical decision-making including selection of targeted therapy (BTK and BCL2 inhibitors). Here, we present the current view on the genomic landscape of CLL, including an update on recent advances with potential for clinical translation. We discuss different state-of-the-art technologies that are applied to enable precision diagnostics in CLL and highlight important genomic markers with current prognostic and/or predictive impact as well as those of prospective clinical relevance. In the coming years, it will be important to develop more comprehensive genomic analyses that can capture all types of relevant genetic aberrations, but also to develop highly sensitive assays to detect minor mutations that affect therapy response or confer resistance to targeted therapies. Finally, we will bring up the potential of new technologies and multi-omics analysis to further subclassify the disease and facilitate implementation of precision medicine approaches in this still incurable disease

Recent revelations and future directions using single-cell technologies in chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) is a clinically and biologically heterogeneous disease with varying outcomes. In the last decade, the application of next-generation sequencing technologies has allowed extensive mapping of disease-specific genomic, epigenomic, immunogenetic, and transcriptomic signatures linked to CLL pathogenesis. These technologies have improved our understanding of the impact of tumor heterogeneity and evolution on disease outcome, although they have mostly been performed on bulk preparations of nucleic acids. As a further development, new technologies have emerged in recent years that allow high-resolution mapping at the single-cell level. These include single-cell RNA sequencing for assessment of the transcriptome, both of leukemic and non-malignant cells in the tumor microenvironment; immunogenetic profiling of B and T cell receptor rearrangements; single-cell sequencing methods for investigation of methylation and chromatin accessibility across the genome; and targeted single-cell DNA sequencing for analysis of copy-number alterations and single nucleotide variants. In addition, concomitant profiling of cellular subpopulations, based on protein expression, can also be obtained by various antibody-based approaches. In this review, we discuss different single-cell sequencing technologies and how they have been applied so far to study CLL onset and progression, also in response to treatment. This latter aspect is particularly relevant considering that we are moving away from chemoimmunotherapy to targeted therapies, with a potentially distinct impact on clonal dynamics. We also discuss new possibilities, such as integrative multi-omics analysis, as well as inherent limitations of the different single-cell technologies, from sample preparation to data interpretation using available bioinformatic pipelines. Finally, we discuss future directions in this rapidly evolving field.</p

Recent revelations and future directions using single-cell technologies in chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) is a clinically and biologically heterogeneous disease with varying outcomes. In the last decade, the application of next-generation sequencing technologies has allowed extensive mapping of disease-specific genomic, epigenomic, immunogenetic, and transcriptomic signatures linked to CLL pathogenesis. These technologies have improved our understanding of the impact of tumor heterogeneity and evolution on disease outcome, although they have mostly been performed on bulk preparations of nucleic acids. As a further development, new technologies have emerged in recent years that allow high-resolution mapping at the single-cell level. These include single-cell RNA sequencing for assessment of the transcriptome, both of leukemic and non-malignant cells in the tumor microenvironment; immunogenetic profiling of B and T cell receptor rearrangements; single-cell sequencing methods for investigation of methylation and chromatin accessibility across the genome; and targeted single-cell DNA sequencing for analysis of copy-number alterations and single nucleotide variants. In addition, concomitant profiling of cellular subpopulations, based on protein expression, can also be obtained by various antibody-based approaches. In this review, we discuss different single-cell sequencing technologies and how they have been applied so far to study CLL onset and progression, also in response to treatment. This latter aspect is particularly relevant considering that we are moving away from chemoimmunotherapy to targeted therapies, with a potentially distinct impact on clonal dynamics. We also discuss new possibilities, such as integrative multi-omics analysis, as well as inherent limitations of the different single-cell technologies, from sample preparation to data interpretation using available bioinformatic pipelines. Finally, we discuss future directions in this rapidly evolving field

Experimental validation of an electronic counting device to determine flight activity of honey bees (Apis mellifera L.)

Ein Funktionsprototyp des Bienenzählers BeeCheck sollte in dieser Arbeit auf seine Genauigkeit hin überprüft werden, um seine Tauglichkeit für den wissenschaft­lichen Einsatz zu validieren. Hierzu wurden zwei unterschiedliche Ansätze verfolgt: (i) Vergleich der elektronischen Daten des Zählgerätes durch Videoaufnahmen von Ein- und Ausflügen mit manueller Auswertung durch einen Beobachter sowie (ii) die Validierung mittels „Räubertest“ im bienendichten Zelt. Die Ergebnisse zeigten eine zu erwartende Temperatur Abhängigkeit der Flug­aktivität sowie die Fehleranfälligkeit bei gewissen Aktivitäten am Flugloch. So waren unterschiedliche Geschwindigkeiten, sich entgegenkommende oder im Flugloch verharrende Bienen, sowie sich vor- und rückwärts bewegende Bienen eine Herausforderung für den Algorithmus, der aus den gemessenen Sensordaten die Bienentransaktionen ableitet. Um diese Grenzfälle zu minimieren und die Zählgenauigkeit zu erhöhen, ist es notwendig den Algorithmus entsprechend korrektiv anzupassen. Dies soll im Folgeprojekt „Etablierung digitaler Indikatoren der Bienenvitalität in Agrarlandschaften – V-I-Bee“ angegangen werden.In this work, a functional prototype of the BeeCheck counting device was evaluated for its accuracy to validate its suitability for scientific purposes. Two different approaches were applied: (i) we manually compared electronic data of the counting device by video recordings of entry and exit events, and (ii) by using the so-called “robber’s test” in a tunnel tent. The results showed an expected temperature dependency of the general flight activity. Difficulties occurred with certain activities at the hive entrance. The various running speeds of individuals, approaching or stuck bees, and bees moving back and forth in the tube were a challenge for sensor technology and the mathematical algorithm. To minimize such mistakes and to increase the counting accuracy, it is necessary to correct the algorithm accordingly. This will be addressed in the “V-I-Bee” follow-up project and future perspectives of using an improved counting device are discussed

Normalization of Illumina Infinium whole-genome SNP data improves copy number estimates and allelic intensity ratios

<p>Abstract</p> <p>Background</p> <p>Illumina Infinium whole genome genotyping (WGG) arrays are increasingly being applied in cancer genomics to study gene copy number alterations and allele-specific aberrations such as loss-of-heterozygosity (LOH). Methods developed for normalization of WGG arrays have mostly focused on diploid, normal samples. However, for cancer samples genomic aberrations may confound normalization and data interpretation. Therefore, we examined the effects of the conventionally used normalization method for Illumina Infinium arrays when applied to cancer samples.</p> <p>Results</p> <p>We demonstrate an asymmetry in the detection of the two alleles for each SNP, which deleteriously influences both allelic proportions and copy number estimates. The asymmetry is caused by a remaining bias between the two dyes used in the Infinium II assay after using the normalization method in Illumina's proprietary software (BeadStudio). We propose a quantile normalization strategy for correction of this dye bias. We tested the normalization strategy using 535 individual hybridizations from 10 data sets from the analysis of cancer genomes and normal blood samples generated on Illumina Infinium II 300 k version 1 and 2, 370 k and 550 k BeadChips. We show that the proposed normalization strategy successfully removes asymmetry in estimates of both allelic proportions and copy numbers. Additionally, the normalization strategy reduces the technical variation for copy number estimates while retaining the response to copy number alterations.</p> <p>Conclusion</p> <p>The proposed normalization strategy represents a valuable tool that improves the quality of data obtained from Illumina Infinium arrays, in particular when used for LOH and copy number variation studies.</p

TP53 aberrations in chronic lymphocytic leukemia: an overview of the clinical implications of improved diagnostics

Chronic lymphocytic leukemia is associated with a highly heterogeneous disease course in terms of clinical outcomes and responses to chemoimmunotherapy. This heterogeneity is partly due to genetic aberrations identified in chronic lymphocytic leukemia cells such as mutations of TP53 and/or deletions in chromosome 17p [del(17p)], resulting in loss of one TP53 allele. These aberrations are associated with markedly decreased survival and predict impaired response to chemoimmunotherapy thus being among the strongest predictive markers guiding treatment decisions in chronic lymphocytic leukemia. Clinical trials demonstrate the importance of accurately testing for TP53 aberrations [both del(17p) and TP53 mutations] before each line of treatment to allow for appropriate treatment decisions that can optimize patient outcomes. The current report reviews the diagnostic methods to better detect TP53 disruption, the role of TP53 aberrations in treatment decisions and current therapies available for patients with chronic lymphocytic leukemia carrying these abnormalities. The standardization in sequencing technologies for accurate identification of TP53 mutations and the importance of continued evaluation of TP53 aberrations throughout initial and subsequent lines of therapy remain unmet clinical needs as new therapeutic alternatives become availabl

Incidence and time trends of second primary malignancies after non-Hodgkin lymphoma:a Swedish population-based study

Considering treatment changes and an improved prognosis of non-Hodgkin lymphoma (NHL) over time, knowledge regarding long-term health outcomes, including late effects of treatment, has become increasingly important. We report on time trends of second primary malignancies (SPMs) in Swedish NHL patients, encompassing the years before as well as after the introduction of anti-CD20 antibody therapy. We identified NHL patients in the Swedish Cancer Register 1993 to 2014 and matched comparators from the Swedish Total Population Register. The matched cohort was followed through 2017. By linking to the Swedish Lymphoma Register, subcohort analyses by NHL subtype were performed. Flexible parametric survival models were used to estimate hazard ratios (HRs) with 95% confidence intervals (CIs) of SPM among patients and comparators. Among 32 100 NHL patients, 3619 solid tumors and 217 myelodysplastic syndrome (MDS)/acute myeloid leukemia (AML) cases were observed, corresponding to a 40% higher rate of solid tumors (HR(solid tumors) = 1.4; 95% CI, 1.4-1.5) and a 5-fold higher rate of MDS/AML (HR(MDS/AML )= 5.2; 95% CI, 4.4-6.2) than for comparators. Overall, the observed excess risks for solid tumors or MDS/AML remained stable over the study period, except for follicular lymphoma, where the excess rate of MDS/AML attenuated with time (P for trend = .012). We conclude that NHL survivors have an increased risk of both solid tumors and hematologic malignancies, in particular MDS/AML. Stable excess risks over time indicate that contemporary treatment standards are not associated with modified SPM risk. Encouragingly, decreasing rates of MDS/AML were noted among patients with follicular lymphoma, possibly due to the increasing use of nonchemotherapy-based treatments

Segmentation-based detection of allelic imbalance and loss-of-heterozygosity in cancer cells using whole genome SNP arrays

A strategy is presented for detection of loss-of-heterozygosity and allelic imbalance in cancer cells from whole genome SNP genotyping data

Quantification of Normal Cell Fraction and Copy Number Neutral LOH in Clinical Lung Cancer Samples Using SNP Array Data

Technologies based on DNA microarrays have the potential to provide detailed information on genomic aberrations in tumor cells. In practice a major obstacle for quantitative detection of aberrations is the heterogeneity of clinical tumor tissue. Since tumor tissue invariably contains genetically normal stromal cells, this may lead to a failure to detect aberrations in the tumor cells.Using SNP array data from 44 non-small cell lung cancer samples we have developed a bioinformatic algorithm that accurately models the fractions of normal and tumor cells in clinical tumor samples. The proportion of normal cells in combination with SNP array data can be used to detect and quantify copy number neutral loss-of-heterozygosity (CNNLOH) in the tumor cells both in crude tumor tissue and in samples enriched for tumor cells by laser capture microdissection.Genome-wide quantitative analysis of CNNLOH using the CNNLOH Quantifier method can help to identify recurrent aberrations contributing to tumor development in clinical tumor samples. In addition, SNP-array based analysis of CNNLOH may become important for detection of aberrations that can be used for diagnostic and prognostic purposes

Whole-genome informed circulating tumor DNA analysis by multiplex digital PCR for disease monitoring in B-cell lymphomas: a proof-of-concept study

IntroductionAnalyzing liquid biopsies for tumor-specific aberrations can facilitate detection of measurable residual disease (MRD) during treatment and at follow-up. In this study, we assessed the clinical potential of using whole-genome sequencing (WGS) of lymphomas at diagnosis to identify patient-specific structural (SVs) and single nucleotide variants (SNVs) to enable longitudinal, multi-targeted droplet digital PCR analysis (ddPCR) of cell-free DNA (cfDNA).MethodsIn 9 patients with B-cell lymphoma (diffuse large B-cell lymphoma and follicular lymphoma), comprehensive genomic profiling at diagnosis was performed by 30X WGS of paired tumor and normal specimens. Patient-specific multiplex ddPCR (m-ddPCR) assays were designed for simultaneous detection of multiple SNVs, indels and/or SVs, with a detection sensitivity of 0.0025% for SV assays and 0.02% for SNVs/indel assays. M-ddPCR was applied to analyze cfDNA isolated from serially collected plasma at clinically critical timepoints during primary and/or relapse treatment and at follow-up.ResultsA total of 164 SNVs/indels were identified by WGS including 30 variants known to be functionally relevant in lymphoma pathogenesis. The most frequently mutated genes included KMT2D, PIM1, SOCS1 and BCL2. WGS analysis further identified recurrent SVs including t(14;18)(q32;q21) (IGH::BCL2), and t(6;14)(p25;q32) (IGH::IRF4). Plasma analysis at diagnosis showed positive circulating tumor DNA (ctDNA) levels in 88% of patients and the ctDNA burden correlated with baseline clinical parameters (LDH and sedimentation rate, p-value &lt;0.01). While clearance of ctDNA levels after primary treatment cycle 1 was observed in 3/6 patients, all patients analyzed at final evaluation of primary treatment showed negative ctDNA, hence correlating with PET-CT imaging. One patient with positive ctDNA at interim also displayed detectable ctDNA (average variant allele frequency (VAF) 6.9%) in the follow-up plasma sample collected 2 years after final evaluation of primary treatment and 25 weeks before clinical manifestation of relapse.ConclusionIn summary, we demonstrate that multi-targeted cfDNA analysis, using a combination of SNVs/indels and SVs candidates identified by WGS analysis, provides a sensitive tool for MRD monitoring and can detect lymphoma relapse earlier than clinical manifestation