Next-generation sequencing: The future of chronic lymphocytic leukaemia (CLL) genomics?

Chronic lymphocytic leukaemia (CLL) is the most common form of adult leukaemia in the USA and in Europe, typically presenting later in life with a mean diagnosis age of 72 years¹. CLL presents an extremely heterogeneous clinical course with some patients being asymptomatic living for decades without treatment while others may present an aggressive variant with rapid progression. Thus, identifying key disease-associated biomarkers is crucial for understanding CLL classification and progression.

In clinical settings, the induction of treatment for patients with CLL may depend upon their symptoms and risk of disease progression². Established clinical-staging systems rely on evaluating haematological or pathophysiological features^3,4 and can also include the assessment of leukaemia cells with genetic aberrations⁵. Testing for genetic aberrations has typically primarily relied on fluorescence in situ hybridisation (FISH) and occasionally, array testing to aid in the prognosis and treatment of CLL. However, the rapid development of genomic techniques has greatly expanded our understanding and identification of novel prognostic markers for CLL.

The use of next-generation sequencing (NGS) techniques to assess these markers can greatly complement existing approaches and provide deeper insights into disease pathology and likely progression.

Current guidelines for CLL diagnosis

The International Workshop on CLL (iwCLL) published updated guidelines in 2018 for the diagnosis, treatment, response assessment and supportive management of patients with CLL².

These guidelines reflect recent advances in the genomic landscape of the disease coupled with the increased availability of novel targeted agents with impressive efficacy. Key diagnostic and prognostic criteria recommended by the iwCLL guidelines include:

• The use of complete blood counts and immunophenotyping to confirm the presence of a minimum of 5000 B lymphocytes/µL of blood, sustained for at least 3 months
• The use of FISH to identify common genetic lesions
• Genetic sequencing to identify the mutational status of certain genes such as TP53
• Serum markers such as β₂-microglobulin for predicting overall survival or progression-free survival

These assessments provide essential insights into the genetic and molecular landscape of the disease, crucial for making well-informed treatment decisions.

Understanding CLL diagnosis: Traditional methods

Since approximately 80% of patients with CLL have at least one chromosomal abnormality⁶, technologies like FISH and microarrays are often used to provide insight into disease-relevant aberrations with high specificity.

Fluorescence in situ hybridisation (FISH)

Over the last 20 years, FISH analysis has become the gold standard for cytogenetic risk stratification in CLL. This approach uses DNA probes labelled with fluorescent dyes to bind targeted chromosome sequences within sampled cells, revealing disease-related chromosomal abnormalities via fluorescent signals. CLL FISH panels normally employ probes for the most common chromosomal aberrations among CLL patients, including deletions of 13q, 17p, 11q, and trisomy 12.

Array-based cytogenetic profiling

Although less common than FISH, microarrays can also be harnessed for genetic profiling as part of CLL diagnoses and patient risk stratification. Modern array technology can screen for copy number variations (CNVs) and loss of heterozygosity (LOH) across the entire genome in a single experiment. Arrays provide more coverage than a FISH panel and can detect multiple aberrations, but they can also inundate clinicians with unnecessary information and are unable to detect balanced translocations or inversions. 

While both technologies provide an enhanced picture of the CLL genomic landscape, it’s becoming ever more important to deploy further technologies to support in the detection of a broader range of genomic aberrations.

Expanding our understanding of the CLL genomic landscape

Over the past decade, NGS technologies have revolutionised the understanding of CLL's genomic landscape, identifying more than 50 genetic lesions that are linked to disease outcome, including BIRC3, SF3B1, TP53 and XPO1 mutations, amongst others^7-9.

Due to this genetic heterogeneity, current CLL analysis strategies require multiple methods to obtain a comprehensive genetic picture and often use microarray or FISH to detect structural abnormalities in combination with NGS for somatic variants.

NGS panels simplify this workflow as they can simultaneously detect different types of genomic aberrations, including single nucleotide variants (SNVs), insertions/deletions (indels), CNVs and structural variants. By testing for multiple variants in a single run it is possible to rapidly define the somatic mutation profile of samples, which can then be used to understand the likely disease course, progression and aid research into novel treatment strategies.

Watch our video to learn more about transitioning to NGS panels

Transition to NGS

As research continues to highlight the complexity of CLL, it’s crucial that technologies deployed in further developing our understanding of CLL have the increased capacity and accuracy to detect key disease-associated biomarkers. Targeted capture-based NGS panels, such as the SureSeq™ CLL + CNV V3 Panel, provide researchers with a tool that comprehensively and accurately detects the most relevant SNVs and CNVs simultaneously for multiple samples in a single run. This NGS panel offers several advantages over traditional technologies, including higher coverage of regions of interest (ROI) and the ability to custom design and screen many genes and samples simultaneously.

Designed in collaboration with leading cancer experts the enhanced SureSeq CLL + CNV V3 Panel design unlocks more expansive genetic profiling of your samples. Our panel allows you to target 16 key disease-associated genes and 5 chromosomal regions implicated in CLL progression (Table 1), including enhanced TP53 variant detection.

Table 1: The SureSeq CLL + CNV V3 Panel targets the 5 most common chromosomal regions implicated in CLL and 16 key disease-associated genes, plus the SRY gene and 24 SNPs for easy sample tracking

The SureSeq CLL + CNV V3 Panel alleviates the burden of running multiple assays and streamlines CLL research to a faster sample-to-result process. By partnering with OGT, we can provide the tools, expert support, and streamlined workflow to help you maximise the potential of your CLL research.

Discover how to streamline your CLL research using the SureSeq CLL + CNV V3 NGS Panel

References

1. Eichhorst B et al. Annals of Oncology 2021;32:23–33. doi: 1016/j.annonc.2020.09.019.
2. Hallek M et al. Blood 2018;131:2745–2760. doi: 1182/blood-2017-09-806398.
3. Binet JL et al. Cancer 1981;48:198–206. doi: 1002/1097-0142(19810701)48:1<198::aid-cncr2820480131>3.0.co;2-v.
4. Rai KR et al. Blood 1975;46:219–234.
5. The International CLL-IPI working group. The Lancet Oncology 2016;17:779–790. doi: 1016/S1470-2045(16)30029-8.
6. Puiggros A et al. Biomed Research International 2014;2014:435983. doi: 1155/2014/435983.
7. Puente XS et al. Nature 2015;526:519–524. doi: 1038/nature14666.
8. Landau DA et al. Nature 2015;526:525–530. doi: 1038/nature15395.
9. Mollstedt J et al. Frontiers in Oncology 2023;13:1146486. doi: 3389/fonc.2023.1146486