Unveiling the dynamics and molecular landscape of a rare chronic lymphocytic leukemia subpopulation driving refractoriness: insights from single-cell RNA sequencing.

Early identification of resistant cancer cells is currently a major challenge, as their expansion leads to refractoriness. To capture the dynamics of these cells, we made a comprehensive analysis of disease progression and treatment response in a chronic lymphocytic leukemia (CLL) patient using a combination of single-cell and bulk genomic methods. At diagnosis, the patient presented with unfavorable genetic markers, including notch receptor 1 (NOTCH1) mutation and loss(11q). The initial and subsequent treatment lines did not lead to a durable response and the patient developed refractory disease. Refractory CLL cells featured substantial dysregulation in B-cell phenotypic markers such as human leukocyte antigen (HLA) genes, immunoglobulin (IG) genes, CD19 molecule (CD19), membrane spanning 4-domains A1 (MS4A1; previously known as CD20), CD79a molecule (CD79A) and paired box 5 (PAX5), indicating B-cell de-differentiation and disease transformation. We described the clonal evolution and characterized in detail two cell populations that emerged during the refractory disease phase, differing in the presence of high genomic complexity. In addition, we successfully tracked the cells with high genomic complexity back to the time before treatment, where they formed a rare subpopulation. We have confirmed that single-cell RNA sequencing enables the characterization of refractory cells and the monitoring of their development over time.

Integrative NGS testing reveals clonal dynamics of adverse genomic defects contributing to a natural progression in treatment-naïve CLL patients.

Large-scale next-generation sequencing (NGS) studies revealed extensive genetic heterogeneity, driving a highly variable clinical course of chronic lymphocytic leukaemia (CLL). The evolution of subclonal populations contributes to diverse therapy responses and disease refractoriness. Besides, the dynamics and impact of subpopulations before therapy initiation are not well understood. We examined changes in genomic defects in serial samples of 100 untreated CLL patients, spanning from indolent to aggressive disease. A comprehensive NGS panel LYNX, which provides targeted mutational analysis and genome-wide chromosomal defect assessment, was employed. We observed dynamic changes in the composition and/or proportion of genomic aberrations in most patients (62%). Clonal evolution of gene variants prevailed over the chromosomal alterations. Unsupervised clustering based on aberration dynamics revealed four groups of patients with different clinical behaviour. An adverse cluster was associated with fast progression and early therapy need, characterized by the expansion of TP53 defects, ATM mutations, and 18p- alongside dynamic SF3B1 mutations. Our results show that clonal evolution is active even without therapy pressure and that repeated genetic testing can be clinically relevant during long-term patient monitoring. Moreover, integrative NGS testing contributes to the consolidated evaluation of results and accurate assessment of individual patient prognosis.

Next-Generation Sequencing-Based Clonality Assessment of Ig Gene Rearrangements: A Multicenter Validation Study by EuroClonality-NGS.

Ig gene (IG) clonality analysis has an important role in the distinction of benign and malignant B-cell lymphoid proliferations and is mostly performed with the conventional EuroClonality/BIOMED-2 multiplex PCR protocol and GeneScan fragment size analysis. Recently, the EuroClonality-NGS Working Group developed a method for next-generation sequencing (NGS)-based IG clonality analysis. Herein, we report the results of an international multicenter biological validation of this novel method compared with the gold standard EuroClonality/BIOMED-2 protocol, based on 209 specimens of reactive and neoplastic lymphoproliferations. NGS-based IG clonality analysis showed a high interlaboratory concordance (99%) and high concordance with conventional clonality analysis (98%) for the molecular conclusion. Detailed analysis of the individual IG heavy chain and kappa light chain targets showed that NGS-based clonality analysis was more often able to detect a clonal rearrangement or yield an interpretable result. NGS-based and conventional clonality analysis detected a clone in 96% and 95% of B-cell neoplasms, respectively, and all but one of the reactive cases were scored polyclonal. We conclude that NGS-based IG clonality analysis performs comparable to conventional clonality analysis. We provide critical parameters for interpretation and discuss a first step toward a quantitative scoring approach for NGS clonality results. Considering the advantages of NGS-based clonality analysis, including its high sensitivity and possibilities for accurate clonal comparison, this supports implementation in diagnostic practice.