Comprehensive multi-omics analysis categorises distinct pathogenic processes in CLL

Comprehensive multi-omics analysis categorises distinct pathogenic processes in CLL
Fig. 1: Composition and relationship of CLL subtypes in clustered data. a Schematic representation for analysis, identification of CLL subtypes in the CLL8, and confirmation in the REACH cohort. The four largest clusters (GI, (I)GI, EMT-L, (I)EMT-L), and associations of NRIP1 with the inflammatory or tri(12) with the EBF1-r signature were also identified in the independent validation cohort of the REACH trial. Co-clustering of GI/(I)GI and EMT-L/(I)EMT-L cases in the REACH cohort supports the selection of subgroup-specific characteristics during treatment. b Heatmap showing the consensus clustering for k = 6 used for defining CLL subtypes (n = 337). The distribution of genetic characteristics is shown below the heatmap. Significant enrichment of variables in clusters is observed for del(17p) (p = 0.05), TP53 mutation (p = 0.01), tri(12) (p = 7e−06), del(13q) (p = 0.03), and IGHV mutation status (p = 0.008) (all Fisher’s exact test (two-sided)). TP53 frameshift mutations occur exclusively in GI and splice site mutations in EBF1-r cases. Tri(12) is strongly overrepresented in EBF1-r (72.7%). c Telomere length is significantly different across CLL subtypes (p < 0.001, Kruskal–Wallis test), and shortest length is observed in GI with a median of 3.8 kb (p = 0.003, Mann–Whitney (two-sided), for GI vs. (I)EMT-L) (n = 333). d White blood cell counts are significantly different across CLL subtypes (p < 0.0001, Kruskal-Wallis test), show decreased counts in inflammatory CLL and are lowest in (I)EMT-L with median 61.1 G/L (p < 0.0001, Mann–Whitney (two-sided), for GI vs. (I)EMT-L) (n = 330). For Fig. 1a–d, data within individual figures derives from biologically independent samples. For the boxplots, centerline, box limits, and whiskers represent the median, 25th, and 75th percentiles, and 1.5× interquartile range, respectively. Credit: DOI: 10.1038/s41467-021-25403-y

An international team of researchers has now comprehensively profiled and categorized over 700 tumor samples from patients with chronic lymphocytic leukemia (CLL) by analyzing multiple levels of encoded biologic information.

Through detailed mapping of the derived information, they identified major biologic categories associated with distinct modes of resistance to different treatment combinations.

Besides changes indicating heterogeneous levels of inflammatory activity, the degree of genomic instability turned out to be a major discriminatory feature for the tumor subgroups.

In , high levels of genomic instability increase the likelihood for alterations in the genome and largely depend on the tumors capabilities to recognize and repair acquired DNA-damage.

Genomic instability in CLL has been linked to mutations or chromosomal losses of regions encoding the cellular watchers for genome protection, the so-called tumor suppressor genes.

Tumors exhibiting inactivation of tumor suppressor genes usually have a poor outcome and early detection helps to choose the most appropriate treatments. However, genomic instability also occurs in many CLL cases without such detectable alterations.

As reported by Johannes Bloehdorn (Ulm University) and colleagues in Nature Communications, tumor sample analysis included the assessment of gene mutations, , DNA-methylation, gene and , and associated pathway-signaling activity.

The authors were able to decode the tumor biology and translate the underlying information in a way that makes it possible to categorize tumors irrespective of detectable losses or mutations of tumor suppressor or DNA-repair genes.

The authors further discovered that genomically instable tumors do not just shut down DNA repair but show boosted and highly error-prone repair activity. This further increases accumulation rates of genomic alterations, accelerating the development of resistance.

Another major subgroup identified in this study, showing the lowest degree of , exhibits characteristics observed during the process of metastasis in solid tumors, which were previously not known to build subgroup-specific functional networks in CLL.

CLL cells can reach any part of the body via the bloodstream. Therefore, it appears redundant to develop mechanisms that enable the cell to break free from a tumor to search for a better survival niche, which is represented through the process of metastasis in solid tumors.

However, these uncovered networks may increase the ability for leukemia cells to exit the bloodstream and migrate to lymphoid tissues. Several targeted treatment approaches address related mechanisms and the cells ability to accumulate in lymphoid organs.

The now established tumor classification represent a significant advance in understanding the underlying biology, mechanisms of resistance and ultimately may improve prognostic models for personalized treatment approaches in CLL, and possibly other tumor entities.


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More information: Johannes Bloehdorn et al, Multi-platform profiling characterizes molecular subgroups and resistance networks in chronic lymphocytic leukemia, Nature Communications (2021). DOI: 10.1038/s41467-021-25403-y
Journal information: Nature Communications

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