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Chronic Lymphocytic Leukemia Genomic Study Reveals New Subtypes, Ties to Outcomes

NEW YORK – An international team has characterized the somatic mutation, gene expression, and epigenetic changes that occur within and across chronic lymphocytic leukemia (CLL) subtypes, uncovering alterations with potential prognostic impact.

"Our study has revealed that the genetic and biologic landscape of CLL is more complex than previously appreciated," co-senior and co-corresponding author Gad Getz, bioinformatics director at the Mass General Cancer Center and director of the Broad Institute's cancer genome computational analysis group, said in a statement.

"We are releasing a CLL map 'portal' that is based on the CLL map and will be an interactive website for translational researchers to use as a resource for further investigation — such as learning more about the different drivers and subtypes of CLL," Getz added.

Using genomic, transcriptomic, and epigenomic profiling, researchers at the Massachusetts General Cancer Center, Dana-Farber Cancer Center, and elsewhere assessed mutation, structural variant, gene expression, and regulatory features in pre-treatment, post-treatment, or treatment refractory/relapsed tumor samples from 1,148 individuals with CLL or monoclonal B cell lymphocytosis. Their results were published in Nature Genetics on Thursday.

Nearly 1,100 of the samples were subjected to exome or whole-genome sequencing, while 712 were assessed with RNA sequencing, and DNA methylation profiling was done on 999 samples.

"This large dataset enabled more complete delineation of the biological underpinnings of CLL and its molecular subtypes," the authors explained.

The team's results highlighted 202 suspected driver genes — impacted by recurrent alterations ranging from single nucleotide changes or small insertions or deletions to structural variants and DNA methylation shifts — that appeared to drive CLL, including 109 suspected driver mutations not linked to the blood and bone marrow malignancy in the past.

"The number of previously unrecognized putative drivers was doubled, thus achieving a more complete genetic basis for this cancer," the authors reported. "These alterations highlight important cellular pathways not previously impacted by candidate drivers that may provide opportunities for development of new therapies in the future."

For example, the investigators identified copy number mutations or structural variants that distinguished CLL subtypes with or without mutations in the immunoglobulin gene heavy-chain variable region (IGHV) through an analysis of 512 mutated IGHV (M-CLL) and 459 IGHV-unmutated CLL tumors.

"Despite lower genetic complexity, M-CLL displayed increased transcriptional diversity segregating mainly into four [expression clusters], which had different proliferative histories," the authors explained, noting that while some of the expression clusters did coincide with established genetic, epitype (epigenetic groups), or IGHV markers, "none of these previously defined groups completely captured the phenotypic diversity in the expression profiles."

The team noted that specific driver gene changes within IGHV subtypes appeared to correspond to clinical outcomes in CLL, as did drivers found through mutation, structural variant, gene expression, or methylation analyses, though combining the different data streams appeared to offer the most complete view of the disease.

"Through integration of harmonized multiomic data, this work has expanded the molecular map of CLL and provided additional insights into its biological and clinical heterogeneity," the authors wrote.

The investigators are making the new CLL omics data available to other researchers, along with corresponding clinical data, in an effort to unearth still other insights that may improve the understanding, management, or treatment of CLL.

"Such a CLL map could eventually be leveraged in the clinic, wherein the genomic features of new patients can be compared with the treatments and outcomes of patients with similar genetic profiles," co-senior and co-corresponding author Catherine Wu, a professor of medicine at Harvard Medical School and chief of the stem cell transplantation and cellular therapies division at Dana-Farber, said in a statement.

"This profiling could potentially help more accurately tailor prognosis and treatment of a new patient based on their particular molecular features, getting closer to precision medicine," Wu wrote.

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