Whole-genome sequencing of chronic lymphocytic leukemia identifies subgroups with distinct biological and clinical features

Robbe, Pauline; Ridout, Kate; Dreau, Hélène; Kinnersley, Ben; Denny, Nicholas; Chubb, Daniel; Appleby, Niamh; Cutts, Anthony; Cornish, Alex J.; Lopez-Pascua, Laura; Clifford, Ruth; Burns, Adam; Stamatopoulos, Basile; Cabes, Maite; Alsolami, Reem; Antoniou, Pavlos; Oates, Melanie; Cavalieri, Doriane; Ambrose, J. C.; Arumugam, Prabhu; Bevers, R.; Bleda, Marta; Boardman-Pretty, F.; Boustred, C. R.; Brittain, Helen; Brown, Matthew A.; Caulfield, Marc J.; Chan, G. C.; Fowler, Tom; Giess, Adam; Hamblin, Angela; Henderson, Shirley; Hubbard, Tim; Jackson, R.; Jones, Louise; Kasperavičiūtė, Dalia; Kayikci, Melis; Kousathanas, Athanasios; Lahnstein, L.; Leigh, Sarah; Leong, I. U. S.; López, F. J. Ruiz; Maleady‐Crowe, F.; McEntagart, Meriel; Minneci, Federico; Moutsianas, Loukas; Mueller, Michael; Murugaesu, Nirupa; Need, Anna C.; O′Donovan, Peter; Odhams, C. A.; Patch, Christine; Perez-Gil, D.; Pereira, Mariana Buongermino; Pullinger, J.; Rahim, T.; Rendon, Augusto; Rogers, T.; Savage, K.; Sawant, K.; Scott, Richard; Siddiq, Afshan; Sieghart, A.; Smith, Sean; Sosinsky, Alona; Stuckey, Alexander; Tanguy, M.; Tavares, Ana Lisa Taylor; Thomas, Ellen; Thompson, S. R.; Tucci, Arianna; Welland, M. J.; Williams, Eleanor; Witkowska, K.; Wood, Scott; Allan, James; Bisshopp, Garry; Blakemore, Stuart J.; Boultwood, Jacqueline; Bruce, David; Buffa, Francesca M.; Buggins, Andrea Pepper née; Cohen, Gerald M.; Cwynarski, Kate; Dearden, Claire; Dillon, Richard; Ennis, Sarah; Falciani, Francesco; Follows, George; Forconi, Francesco; Forster, Jade; Fox, Christopher P.; Gribben, John G.; Hockaday, Anna; Howard, Dena; Jackson, Andrew; Kalakonda, Nagesh; Khan, Umair; Law, Philip; Lefèvre, Pascal; Lin, Ke; Maseno, Sandra; Moss, Paul; Packham, Graham; Palles, Claire; Parker, Helen; Patten, Piers; Pellagatti, Andrea; Pratt, Guy; Ramsay, Alan D.; Rawstron, Andy; Rose-Zerilli, Matthew; Slupsky, Joseph R.; Stanković, Tatjana; Steele, Andrew J.; Strefford, Jonathan C.; Varadarajan, Shankar; Vavoulis, Dimitrios V; Wagner, Simon D.; Westhead, David; Wordsworth, Sarah; Zhuang, Jack; Gibson, Jane; Prabhu, Anika V.; Schweßinger, Ron; Jennings, Daisy; James, Terena; Maheswari, Uma; Duran-Ferrer, Martí; Carninci, Piero; Knight, Samantha Jl; Månsson, Robert; Hughes, Jim R.; Davies, James O. J.; Ross, Mark T.; Bentley, David; Strefford, Jonathan C.; Devereux, Stephen; Pettitt, Andrew R.; Hillmen, Peter; Caulfield, Mark J.; Houlston, Richard S.; Martín‐Subero, José I.; Schuh, Anna

doi:10.1038/s41588-022-01211-y

Cited by 31 publications

(27 citation statements)

References 86 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the last 10 years, NGS-based technologies have been used to characterize the genomic landscape in CLL, which has represented a first critical step in mapping novel genomic biomarkers (27,30,32,33,60,94). Based on these studies, a long list of potentially clinically FIGURE 4 Precision diagnostics in CLL, present status and future directions.…”

Section: Discussionmentioning

confidence: 99%

“…A considerable advantage with WGS is that a complete genomic profile is provided, detecting all types of genomic alterations, e.g., SNVs/indels, CNVs, gene fusions and large structural aberrations, including translocations, at the same time (Figure 4). Additionally, WGS can also detect karyotypic complexity and IGHV gene SHM status as well as non-coding mutations e.g., the previously mentioned 3' UTR mutations in NOTCH1, which have been shown to function as driver mutations (32,94,97). Finally, having access to a complete genomic profile of a patient prior to start of treatment would also be beneficial for research purposes, e.g., for the detection of novel genetic aberrations linked to disease progression and therapy resistance.…”

Section: Discussionmentioning

confidence: 99%

“…In another recent study, the authors integrated genomic, transcriptomic and ATAC-seq data and identified 5 genomic subgroups (GSs) that were linked to certain genomic aberrations, expression signatures and outcome. u-GS1 was characterized by the presence of TP53 aberrations, short telomeres and MAPK/PI3K mutations, whereas u-GS2 was enriched by ATM/ BIRC3 alterations, and mutations in DNA damage response genes (94,100).…”

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

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

Mansouri

Rosenquist

2023

Front. Oncol.

View full text Add to dashboard Cite

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.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

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

Mansouri

Rosenquist

2023

Front. Oncol.

View full text Add to dashboard Cite

show abstract

“…Another important factor that is not taken into account in this study is the characteristic phenotype of the CLL cells, which are patient-specific and can be potentially affected by the CLL subtype (unmutated or mutated CLL, i.e. U-CLL, M-CLL (78, 79)), related to their cell of origin, which can impact the aggressiveness of the disease. Moreover, we cannot exclude an effect of age or sex of the patient.…”

Section: Limitations Of the Studymentioning

confidence: 99%

An Agent-Based Model of Monocyte Differentiation into Tumour-Associated Macrophages in Chronic Lymphocytic Leukemia

Verstraete

Marku

Domagala

et al. 2021

Preprint

View full text Add to dashboard Cite

Monocyte-derived macrophages are immune cells which help maintain tissue homeostasis and defend the organism against pathogens. In solid tumours, recent studies have uncovered complex macrophage populations, among which tumour-associated macrophages, supporting tumorigenesis through multiple cancer hallmarks such as immunosuppression, angiogenesis or matrix remodelling. In the case of chronic lymphocytic leukemia, these macrophages are known as nurse-like cells and have been shown to protect leukemic cells from spontaneous apoptosis and contribute to their chemoresistance. We propose an agent-based model of monocytes differentiation into nurse-like cells upon contact with leukemic B cells in-vitro. We studied monocyte differentiation and cancer cells survival dynamics depending on diverse hypotheses on monocytes and cancer cells relative proportions, sensitivity to their surrounding environment and cell-cell interactions. Peripheral blood mononuclear cells from patients were cultured and monitored during 13 days to calibrate the model parameters, such as phagocytosis efficiency, death rates or protective effect from the nurse-like cells. Our model is able to reproduce experimental results and predict cancer cells survival dynamics in a patient-specific manner. Our results shed light on important factors at play in cancer cells survival, highlighting a potentially important role of phagocytosis.

show abstract

“…Today, recurrent genomic alterations have been described in >2000 genes, of which >200 genes have been identified as putative ‘drivers’. Of these, >25 genes are associated with clinically aggressive disease, including ATM, BIRC3, EGR2, NFKBIE , NOTCH1 , SF3B1 , and TP53 , among others ( 9 – 14 ). Moreover, CLL is characterized by the expression of almost identical or ‘stereotyped’ B cell receptor immunoglobulins (BcR IGs) in more than 40% of patients ( 15 ).…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2023

View full text Add to dashboard Cite

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.

show abstract

Whole-genome sequencing of chronic lymphocytic leukemia identifies subgroups with distinct biological and clinical features

Cited by 31 publications

References 86 publications

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

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

An Agent-Based Model of Monocyte Differentiation into Tumour-Associated Macrophages in Chronic Lymphocytic Leukemia

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

Contact Info

Product

Resources

About